Set-Up workspace

There are two possible directories containing sequence data: * /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/rbcL ** this directory is for running the code on UVA’s HPC Rivanna

  • /Users/kelseyschoenemann/Desktop/Bioinformatics/2024-09-27_MiSeq_v3/ITS2 ** this directory is for running the code on my local machine

(you can easily switch between these two directories by selecting the old path, up to & including Bioinformatics, and hit Cmd F to bring up Find & Replace tool, then copy-paste the new path into the Replace box and hit All. There should be 25 replacements if you skip the very first instance above)

Summary of Files / Directories

/scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2 *Ns & primers present (raw files)

/scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/filtN *Ns removed, primers present (pre-filtered)

/scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt *Ns & primers removed (cutadapted)

/scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered *Ns & primers removed and filter & trimmed (filtered)

  • List of primers used * We used plant universal primers: iTru_ITS2_S2F (ATGCGATACTTGGTGTGAAT) & iTru_ITS2_4R (TCCTCCGCTTATTGATATGC) iTru_rbcL2 (TGGCAGCATTYCGAGTAACTC) & iTru_rbcLa-R (GTAAAATCAAGTCCACCRCG)

Load packages

#install packages with BiocManager (if you have anaconda)
# if (!requireNamespace("BiocManager", quietly = TRUE))
#     install.packages("BiocManager")
# BiocManager::install("dada2", version = "3.16")
# BiocManager::install(c("DECIPHER", "ShortRead", "phyloseq")"))
# BiocManager::install("decontam")

library(devtools); packageVersion("devtools")
## Loading required package: usethis
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library(dada2); packageVersion("dada2")
## Loading required package: Rcpp
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library(ShortRead); packageVersion("ShortRead")
## Loading required package: BiocGenerics
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library(ggplot2); packageVersion("ggplot2")
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#library(decontam); packageVersion("decontam")

#devtools::install_github("benjjneb/dada2", ref="v1.16") # change the ref argument to get other versions

Set working directory

setwd("/scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2")
path <- "/scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2" ## CHANGE ME to the directory containing the fastq files.
head(list.files(path, pattern = "*.fastq"))
## [1] "ITS2-2020-6-16-H1_S31_L001_R1_001.fastq"
## [2] "ITS2-2020-6-16-H1_S31_L001_R2_001.fastq"
## [3] "ITS2-2020-6-16-H5_S32_L001_R1_001.fastq"
## [4] "ITS2-2020-6-16-H5_S32_L001_R2_001.fastq"
## [5] "ITS2-2020-6-16-H6_S33_L001_R1_001.fastq"
## [6] "ITS2-2020-6-16-H6_S33_L001_R2_001.fastq"
list.files(path, pattern = "*.fastq")[1]
## [1] "ITS2-2020-6-16-H1_S31_L001_R1_001.fastq"
#R.utils::gunzip(list.files(path), remove=F)
R.utils::isGzipped(list.files(path, pattern = "*.fastq")[1]) # checking that the file is unzipped, FALSE = not gzipped
## [1] FALSE
# intstall R.utils
# library(R.utils)
# lapply(list.files(path, pattern = "*.gz"), FUN=gunzip, remove=F) # unzip all .gz files and don't remove compressed files
# I manually moved all compressed files into a new folder, leaving these unzipped files in the working directory for this script
# commenting out since I only need to unzip once

Prep raw sequence reads

Match forward and reverse reads by sample name. Pre-filter to remove reads with Ns.

Generate matched lists of fwd & rev reads with sample name

Forward and reverse fastq files have the format: ITS2_SAMPLENAME_SXXX_L001_R1_001.fastq and ITS2_SAMPLENAME_SXXX_L001_R2_001.fastq, respectively

For example: ITS2-2020-6-16-H1_S293_L001_R1_001.fastq is the forward reads of ITS2 sample 2020-06-16-H1

fnFs <- sort(list.files(path, pattern = "L001_R1_001.fastq", full.names = TRUE))
fnRs <- sort(list.files(path, pattern = "L001_R2_001.fastq", full.names = TRUE))

#string parsing may have to be altered in your own data if your file names have a different format.

Pre-filter to remove reads with Ns

Ambiguous bases (Ns) in the sequencing reads makes accurate mapping of short primer sequences difficult. Here, remove reads with Ns, but perform no other filtering.

fnFs.filtN <- file.path(path, "filtN", basename(fnFs)) #create directory paths to contain N-filterd files in filtN/ subdirectory within path
fnRs.filtN <- file.path(path, "filtN", basename(fnRs))

Now we can filter out whole sequences and trim parts of sequences based on their quality score. This function takes files from path /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2 and creates new files in filtN folder /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/filtN

filterAndTrim(fnFs, fnFs.filtN, fnRs, fnRs.filtN, maxN = 0, multithread = TRUE, matchIDs = TRUE, compress=FALSE) #eliminates sequences with more than 0 Ns; 
## Some input samples had no reads pass the filter.
#I had an issue with "Mismatched forward and reverse sequence files" but adding the matchID=T parameter fixed it; #I had an issue with the filtN files being compressed somehow so the cutadapt command couldn't read the files ("UnicodeDecodeError: 'utf-8' codec can't decode byte 0x8b in position 1: invalid start byte"), adding the compress = F parameter fixed it (("Or you could just gzip all your files at the beginning." - benjjneb))

Check how much filtering affected read numbers

n=7
#before filterAndTrim
plotQualityProfile(fnFs[n:n]) #checking quality and number of FWD reads of nth sample

plotQualityProfile(fnRs[n:n]) #checking quality and number of REV reads of nth sample

#after filterAndTrim
plotQualityProfile(fnFs.filtN[n:n]) #checking quality and number of FWD reads of nth sample

plotQualityProfile(fnRs.filtN[n:n]) #checking quality and number of REV reads of nth sample

Not every sample made it through the pre-filter to remove reads with Ns

length(file.path(path, "filtN", basename(fnFs))) #length of "fnFs.filtN," created in chunk above (261)
## [1] 262
length(list.files(file.path(path, "filtN"), pattern = "L001_R1_001.fastq", full.names = TRUE)) #length of files actually written to the fnFs.filtN directories (###)
## [1] 257

Updating path names (after samples drop out)

# update directory, since not all samples made it thru the filter
fnFs.filtN <- file.path(path, "filtN", basename(list.files(file.path(path, "filtN"), pattern = "L001_R1_001.fastq", full.names = TRUE))) 
fnRs.filtN <- file.path(path, "filtN", basename(list.files(file.path(path, "filtN"), pattern = "L001_R2_001.fastq", full.names = TRUE)))

Identify primers in reads

Verify the presence and orientation of these primers

#ITS2 primers
FWD <- "ATGCGATACTTGGTGTGAAT"  ## CHANGE ME to your forward primer sequence
REV <- "TCCTCCGCTTATTGATATGC"  ## CHANGE ME...

#to ensure we have the right primers, and the correct orientation of the primers on the reads, we will verify the presence and orientation of these primers in the data

allOrients <- function(primer) {
  # Create all orientations of the input sequence
  require(Biostrings)
  dna <- DNAString(primer)  # The Biostrings works w/ DNAString objects rather than character vectors
  orients <- c(Forward = dna, Complement = complement(dna), Reverse = reverse(dna),
               RevComp = reverseComplement(dna))
  return(sapply(orients, toString))  # Convert back to character vector
}

FWD.orients <- allOrients(FWD)
REV.orients <- allOrients(REV)

FWD.orients #all possible orientations of forward
##                Forward             Complement                Reverse 
## "ATGCGATACTTGGTGTGAAT" "TACGCTATGAACCACACTTA" "TAAGTGTGGTTCATAGCGTA" 
##                RevComp 
## "ATTCACACCAAGTATCGCAT"
REV.orients #...and reverse primers
##                Forward             Complement                Reverse 
## "TCCTCCGCTTATTGATATGC" "AGGAGGCGAATAACTATACG" "CGTATAGTTATTCGCCTCCT" 
##                RevComp 
## "GCATATCAATAAGCGGAGGA"

Count how many times primers appear in reads

We are now ready to count the number of times the primers appear in the forward and reverse read, while considering all possible primer orientations. Identifying and counting the primers on one set of paired end FASTQ files is sufficient, assuming all the files were created using the same library preparation, so we’ll just process the first sample.

primerHits <- function(primer, fn) {
  # Counts number of reads in which the primer is found
  nhits <- vcountPattern(primer, sread(readFastq(fn)), fixed = FALSE)
  return(sum(nhits > 0))
}

#count of primer hits in the nth read
rbind(FWD.ForwardReads = sapply(FWD.orients, primerHits, fn = fnFs.filtN[[n]]),
      FWD.ReverseReads = sapply(FWD.orients, primerHits, fn = fnRs.filtN[[n]]),
      REV.ForwardReads = sapply(REV.orients, primerHits, fn = fnFs.filtN[[n]]),
      REV.ReverseReads = sapply(REV.orients, primerHits, fn = fnRs.filtN[[n]]))
##                  Forward Complement Reverse RevComp
## FWD.ForwardReads   53406          0       0       0
## FWD.ReverseReads       0          0       0       1
## REV.ForwardReads       0          0       0       1
## REV.ReverseReads   50849          0       0       0

Note: Orientation mixups are a common trip-up. If, for example, the REV primer is matching the Reverse reads in its RevComp orientation, then replace REV with its reverse-complement orientation (REV <- REV.orient[[“RevComp”]]) before proceeding.

Remove primers from reads

These primers can be now removed using a specialized primer/adapter removal tool. Here, we use cutadapt for this purpose. Download, installation and usage instructions are available online: http://cutadapt.readthedocs.io/en/stable/index.html

#cutadapt <- "/Users/kelseyschoenemann/opt/anaconda3/envs/cutadaptenv/bin/cutadapt" #CHANGE ME to the cutadapt path on your local machine

cutadapt <- "/home/kls7sg/.local/bin/cutadapt" #for running on Rivanna HPC
system2(cutadapt, args = "--version") # Run shell commands from R

If the above command successfully executed, R has found cutadapt and you are ready to continue following along.

We now create output filenames for the cutadapt-ed files, and define the parameters we are going to give the cutadapt command. The critical parameters are the primers, and they need to be in the right orientation, i.e. the FWD primer should have been matching the forward-reads in its forward orientation, and the REV primer should have been matching the reverse-reads in its forward orientation.

Create directory with updated path names

path.cut <- file.path(path, "cutadapt"); if(!dir.exists(path.cut)) dir.create(path.cut) #create a new folder in the main directory called cutadapt
#/scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt

# fnFs.cut <- file.path(path.cut, basename(fnFs)) #old code #to place fwd reads w/o primers in the new cutadapt directory
# fnRs.cut <- file.path(path.cut, basename(fnRs)) #old code
           length(file.path(path, basename(fnFs)))    # 262 samples with F reads in original directory
## [1] 262
length(list.files(file.path(path, "filtN"), pattern = "L001_R1_001.fastq", full.names = TRUE)) # but only 257 samples passed the filtN filter (removing reads with Ns)
## [1] 257
# figuring out how to create/call directory paths with just retained samples
# basename(list.files(file.path(path, "filtN"), pattern = "L001_R1_001.fastq", full.names = TRUE))[1]
# file.path(path.cut, basename(list.files(file.path(path, "filtN"), pattern = "L001_R1_001.fastq", full.names = TRUE))[1])

# here's an updated directory that only includes destinations for samples/files that still exist
fnFs.cut <- file.path(path.cut, sort(basename(list.files(file.path(path, "filtN"), pattern = "R1_001.fastq", full.names = TRUE)))) #to place forward reads with primers cut (removed) in the new cutadapt directory
fnRs.cut <- file.path(path.cut, sort(basename(list.files(file.path(path, "filtN"), pattern = "R2_001.fastq", full.names = TRUE)))) #to place reverse reads with primers cut (removed) in the new cutadapt directory

Running cutadapt

FWD.RC <- dada2:::rc(FWD) #generate reverse complement of fwd
REV.RC <- dada2:::rc(REV) #...and rev primers

R1.flags <- paste("-g", FWD, "-a", REV.RC) # To flag FWD and reverse-complement of REV for removal from forward reads (R1)
R2.flags <- paste("-G", REV, "-A", FWD.RC) # To flag REV and  reverse-complement of FWD for removal from reverse reads (R2)

# Run Cutadapt to cut flagged sequences from input reads and save cut sequences to output folder
#Warning: A lot of output will be written to the console by cutadapt!

for(i in seq_along(fnFs)) {
  system2(cutadapt, args = c(
    R1.flags, R2.flags, "-n", 2, #-n 2 required to remove FWD & REV from reads
    "-o", fnFs.cut[i], "-p", fnRs.cut[i], # output files
    fnFs.filtN[i], fnRs.filtN[i]) # input files
    )
}

Count primers again

As a sanity check, we will count the presence of primers in the nth cutadapt-ed sample:

rbind(FWD.ForwardReads = sapply(FWD.orients, primerHits, fn = fnFs.cut[[n]]),
      FWD.ReverseReads = sapply(FWD.orients, primerHits, fn = fnRs.cut[[n]]),
      REV.ForwardReads = sapply(REV.orients, primerHits, fn = fnFs.cut[[n]]),
      REV.ReverseReads = sapply(REV.orients, primerHits, fn = fnRs.cut[[n]]))
##                  Forward Complement Reverse RevComp
## FWD.ForwardReads       0          0       0       0
## FWD.ReverseReads       0          0       0       0
## REV.ForwardReads       0          0       0       0
## REV.ReverseReads       0          0       0       0

Success! Primers are no longer detected in the cutadapted reads. The primer-free sequence files are now ready to be analyzed through the DADA2 pipeline.

#Prep the pre-filtered & “cutadapted” sequence reads

Generate matched lists of fwd & rev reads with sample name

Create path names (all samples included)

#the only thing changing from last time is 'path' becomes 'path.cut'
#fnRs <- sort(list.files(path, pattern = "_2.fastq.gz", full.names = TRUE))

cutFs <- sort(list.files(path.cut, pattern = "L001_R1_001.fastq", full.names = TRUE))
cutRs <- sort(list.files(path.cut, pattern = "L001_R2_001.fastq", full.names = TRUE))

Filter and trim “cutadapted” reads with filtering parameters

To store the output files of filtered reads as fastq.gz files, we’re creating another directory /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered

filtFs <- file.path(path.cut, "filtered", basename(cutFs))
filtRs <- file.path(path.cut, "filtered", basename(cutRs))
#recall, the PRE-filter filter:    filterAndTrim(fnFs, fnFs.filtN, fnRs, fnRs.filtN, maxN = 0, multithread = TRUE, matchIDs = T, compress=F) #eliminates sequences with more than 0 Ns

#NOW we filter for more stringent Quality Control
out <- filterAndTrim(cutFs, filtFs, cutRs, filtRs, maxN = 0, maxEE = c(2, 5), minLen = 50, rm.phix = TRUE, compress = TRUE, multithread = TRUE) #changed from default: maxEE=2,5
## Some input samples had no reads pass the filter.
head(out)
##                                         reads.in reads.out
## ITS2-2020-6-16-H1_S31_L001_R1_001.fastq        8         2
## ITS2-2020-6-16-H5_S32_L001_R1_001.fastq        5         3
## ITS2-2020-6-16-H6_S33_L001_R1_001.fastq        2         1
## ITS2-2020-6-17-H2_S34_L001_R1_001.fastq       14         7
## ITS2-2020-6-17-H4_S35_L001_R1_001.fastq       21         8
## ITS2-2020-6-17-H8_S36_L001_R1_001.fastq        7         5
out.table<-as.data.frame(cbind(out,(out[,2]/out[,1])*100))
100-mean((out[,2]/out[,1])*100, na.rm=T) #loose __% of reads on average
## [1] 49.00262

For this dataset, we will use the following filtering parameters:

  • maxN=0 #DADA2 requires sequences contain no Ns and Ns are already removed (this is the default setting)
  • truncQ=2 #trims/truncates reads at the first instance of a bp with quality score =< 2 (this is the default setting)
  • rm.phix=TRUE PhiX (FEE-ex) is a small virus with single-stranded DNA that you can spike in samples to use as control in sequencing #removes these reads in filtering
  • maxEE=2,5 #sets the maximum number of “expected errors” allowed in a read.. c(2,5) sets the parameter for the F & R reads
  • minLen=50 #sets the minimum bp length of reads #gets rid of spurious very low-length sequences
# testing effect of different parameter values
# out.sub <- filterAndTrim(head(cutFs, n=30L), head(filtFs, n=30L), head(cutRs, n=30L), head(filtRs, n=30L), 
#                          maxEE = c(2, 5), minLen = 50, # modify maxEE, minLen here
#                          rm.phix = TRUE, compress = FALSE, multithread = TRUE)
# out.sub.table<-as.data.frame(cbind(out.sub,(out.sub[,2]/out.sub[,1])*100)) # calc perc reads remaining remaining
# summary(out.sub.table)
# 100-mean((out.sub[,2]/out.sub[,1])*100, na.rm=T) #loose __% of reads on average
#
# rm(out.sub, out.sub.table)

Check how much filtering affected read quality profile and read numbers

n=n
#before filterAndTrim
plotQualityProfile(cutFs[n:n]) #checking quality and number of FWD reads of nth sample

#after filterAndTrim
plotQualityProfile(filtFs[n:n]) #checking quality and number of FWD reads of nth sample

Updating sample names (after samples drop out)

# updating sample names for "out"
length(rownames(as.data.frame(out)))
## [1] 262
                                           rownames(as.data.frame(out))
##   [1] "ITS2-2020-6-16-H1_S31_L001_R1_001.fastq"                        
##   [2] "ITS2-2020-6-16-H5_S32_L001_R1_001.fastq"                        
##   [3] "ITS2-2020-6-16-H6_S33_L001_R1_001.fastq"                        
##   [4] "ITS2-2020-6-17-H2_S34_L001_R1_001.fastq"                        
##   [5] "ITS2-2020-6-17-H4_S35_L001_R1_001.fastq"                        
##   [6] "ITS2-2020-6-17-H8_S36_L001_R1_001.fastq"                        
##   [7] "ITS2-2020-6-18-H3_S37_L001_R1_001.fastq"                        
##   [8] "ITS2-2020-6-18-H7_S38_L001_R1_001.fastq"                        
##   [9] "ITS2-2020-6-18-H9_S39_L001_R1_001.fastq"                        
##  [10] "ITS2-2020-6-3-H1_S40_L001_R1_001.fastq"                         
##  [11] "ITS2-2020-6-3-H5_S41_L001_R1_001.fastq"                         
##  [12] "ITS2-2020-6-3-H6_S42_L001_R1_001.fastq"                         
##  [13] "ITS2-2020-6-30-H1_S43_L001_R1_001.fastq"                        
##  [14] "ITS2-2020-6-30-H5_S44_L001_R1_001.fastq"                        
##  [15] "ITS2-2020-6-30-H6_S45_L001_R1_001.fastq"                        
##  [16] "ITS2-2020-6-4-H2_S46_L001_R1_001.fastq"                         
##  [17] "ITS2-2020-6-4-H4_S47_L001_R1_001.fastq"                         
##  [18] "ITS2-2020-6-4-H8_S48_L001_R1_001.fastq"                         
##  [19] "ITS2-2020-6-5-H3_S49_L001_R1_001.fastq"                         
##  [20] "ITS2-2020-6-5-H7_S50_L001_R1_001.fastq"                         
##  [21] "ITS2-2020-6-5-H9_S51_L001_R1_001.fastq"                         
##  [22] "ITS2-2020-7-1-H2_S52_L001_R1_001.fastq"                         
##  [23] "ITS2-2020-7-1-H4_S53_L001_R1_001.fastq"                         
##  [24] "ITS2-2020-7-1-H8_S54_L001_R1_001.fastq"                         
##  [25] "ITS2-2020-7-14-H1_S55_L001_R1_001.fastq"                        
##  [26] "ITS2-2020-7-14-H5_S56_L001_R1_001.fastq"                        
##  [27] "ITS2-2020-7-14-H6_S57_L001_R1_001.fastq"                        
##  [28] "ITS2-2020-7-15-H2_S58_L001_R1_001.fastq"                        
##  [29] "ITS2-2020-7-15-H4_S59_L001_R1_001.fastq"                        
##  [30] "ITS2-2020-7-15-H8_S60_L001_R1_001.fastq"                        
##  [31] "ITS2-2020-7-16-H3_S61_L001_R1_001.fastq"                        
##  [32] "ITS2-2020-7-16-H7_S62_L001_R1_001.fastq"                        
##  [33] "ITS2-2020-7-16-H9_S63_L001_R1_001.fastq"                        
##  [34] "ITS2-2020-7-2-H3_S64_L001_R1_001.fastq"                         
##  [35] "ITS2-2020-7-2-H7_S65_L001_R1_001.fastq"                         
##  [36] "ITS2-2020-7-2-H9_S66_L001_R1_001.fastq"                         
##  [37] "ITS2-2021-6-13-H1_S67_L001_R1_001.fastq"                        
##  [38] "ITS2-2021-6-13-H3_S68_L001_R1_001.fastq"                        
##  [39] "ITS2-2021-6-14-H11_S69_L001_R1_001.fastq"                       
##  [40] "ITS2-2021-6-14-H6_S70_L001_R1_001.fastq"                        
##  [41] "ITS2-2021-6-14-H7_S71_L001_R1_001.fastq"                        
##  [42] "ITS2-2021-6-15-H8_S72_L001_R1_001.fastq"                        
##  [43] "ITS2-2021-6-21-H10_S73_L001_R1_001.fastq"                       
##  [44] "ITS2-2021-6-21-H12_S74_L001_R1_001.fastq"                       
##  [45] "ITS2-2021-6-21-H9_S75_L001_R1_001.fastq"                        
##  [46] "ITS2-2021-6-27-H21_S76_L001_R1_001.fastq"                       
##  [47] "ITS2-2021-6-27-H22_S77_L001_R1_001.fastq"                       
##  [48] "ITS2-2021-6-27-H27_S78_L001_R1_001.fastq"                       
##  [49] "ITS2-2021-6-28-H25_S79_L001_R1_001.fastq"                       
##  [50] "ITS2-2021-6-28-H26_S80_L001_R1_001.fastq"                       
##  [51] "ITS2-2021-6-28-H28_S81_L001_R1_001.fastq"                       
##  [52] "ITS2-2021-6-29-H17_S82_L001_R1_001.fastq"                       
##  [53] "ITS2-2021-6-29-H23_S83_L001_R1_001.fastq"                       
##  [54] "ITS2-2021-6-29-H24_S84_L001_R1_001.fastq"                       
##  [55] "ITS2-2021-6-4-H21_S85_L001_R1_001.fastq"                        
##  [56] "ITS2-2021-6-4-H22_S86_L001_R1_001.fastq"                        
##  [57] "ITS2-2021-6-4-H27_S87_L001_R1_001.fastq"                        
##  [58] "ITS2-2021-6-5-H18_S88_L001_R1_001.fastq"                        
##  [59] "ITS2-2021-6-5-H25_S89_L001_R1_001.fastq"                        
##  [60] "ITS2-2021-6-5-H26_S90_L001_R1_001.fastq"                        
##  [61] "ITS2-2021-6-6-H17_S91_L001_R1_001.fastq"                        
##  [62] "ITS2-2021-6-6-H24_S92_L001_R1_001.fastq"                        
##  [63] "ITS2-2021-6-7-H23_S93_L001_R1_001.fastq"                        
##  [64] "ITS2-2021-7-14-H10_S94_L001_R1_001.fastq"                       
##  [65] "ITS2-2021-7-14-H12_S95_L001_R1_001.fastq"                       
##  [66] "ITS2-2021-7-20-H27_S96_L001_R1_001.fastq"                       
##  [67] "ITS2-2021-7-21-H25_S97_L001_R1_001.fastq"                       
##  [68] "ITS2-2021-7-21-H26_S98_L001_R1_001.fastq"                       
##  [69] "ITS2-2021-7-21-H28_S99_L001_R1_001.fastq"                       
##  [70] "ITS2-2021-7-6-H11_S100_L001_R1_001.fastq"                       
##  [71] "ITS2-2021-7-6-H30_S101_L001_R1_001.fastq"                       
##  [72] "ITS2-2021-7-6-H6_S102_L001_R1_001.fastq"                        
##  [73] "ITS2-2021-7-7-H4_S103_L001_R1_001.fastq"                        
##  [74] "ITS2-2021-7-7-H8_S104_L001_R1_001.fastq"                        
##  [75] "ITS2-2021-7-8-H3_S105_L001_R1_001.fastq"                        
##  [76] "ITS2-2023-6-12-H3_S106_L001_R1_001.fastq"                       
##  [77] "ITS2-2023-6-12-H5_S107_L001_R1_001.fastq"                       
##  [78] "ITS2-2023-6-12-H7_S108_L001_R1_001.fastq"                       
##  [79] "ITS2-2023-6-13-H6_S109_L001_R1_001.fastq"                       
##  [80] "ITS2-2023-6-13-H8_S110_L001_R1_001.fastq"                       
##  [81] "ITS2-2023-6-13-H9_S111_L001_R1_001.fastq"                       
##  [82] "ITS2-2023-6-14-H3_S112_L001_R1_001.fastq"                       
##  [83] "ITS2-2023-6-14-H7_S113_L001_R1_001.fastq"                       
##  [84] "ITS2-2023-6-14-H9_S114_L001_R1_001.fastq"                       
##  [85] "ITS2-2023-6-16-H5_S115_L001_R1_001.fastq"                       
##  [86] "ITS2-2023-6-24-H6_S116_L001_R1_001.fastq"                       
##  [87] "ITS2-2023-6-24-H8_S117_L001_R1_001.fastq"                       
##  [88] "ITS2-2023-6-25-H2_S118_L001_R1_001.fastq"                       
##  [89] "ITS2-2023-6-25-H4_S119_L001_R1_001.fastq"                       
##  [90] "ITS2-2023-6-26-H1_S120_L001_R1_001.fastq"                       
##  [91] "ITS2-2023-6-26-H7_S121_L001_R1_001.fastq"                       
##  [92] "ITS2-2023-6-27-H3_S122_L001_R1_001.fastq"                       
##  [93] "ITS2-2023-6-27-H5_S123_L001_R1_001.fastq"                       
##  [94] "ITS2-2023-6-8-H1_S124_L001_R1_001.fastq"                        
##  [95] "ITS2-2023-6-8-H2_S125_L001_R1_001.fastq"                        
##  [96] "ITS2-2023-6-8-H4_S126_L001_R1_001.fastq"                        
##  [97] "ITS2-2023-6-9-H2_S127_L001_R1_001.fastq"                        
##  [98] "ITS2-2023-6-9-H4_S128_L001_R1_001.fastq"                        
##  [99] "ITS2-2023-7-15-H6_S129_L001_R1_001.fastq"                       
## [100] "ITS2-2023-7-16-H4_S130_L001_R1_001.fastq"                       
## [101] "ITS2-2023-7-17-H1_S131_L001_R1_001.fastq"                       
## [102] "ITS2-2023-7-18-H3_S132_L001_R1_001.fastq"                       
## [103] "ITS2-2023-7-18-H7_S133_L001_R1_001.fastq"                       
## [104] "ITS2-2023-7-29-H5_S134_L001_R1_001.fastq"                       
## [105] "ITS2-2023-7-29-H7_S135_L001_R1_001.fastq"                       
## [106] "ITS2-2023-7-30-H8_S136_L001_R1_001.fastq"                       
## [107] "ITS2-2023-7-30-H9_S137_L001_R1_001.fastq"                       
## [108] "ITS2-2023-7-5-H1_S138_L001_R1_001.fastq"                        
## [109] "ITS2-2023-7-5-H2_S139_L001_R1_001.fastq"                        
## [110] "ITS2-2023-7-5-H4_S140_L001_R1_001.fastq"                        
## [111] "ITS2-2023-7-6-H6_S141_L001_R1_001.fastq"                        
## [112] "ITS2-2023-7-6-H8_S142_L001_R1_001.fastq"                        
## [113] "ITS2-2023-7-6-H9_S143_L001_R1_001.fastq"                        
## [114] "ITS2-2023-7-8-H3_S144_L001_R1_001.fastq"                        
## [115] "ITS2-2023-7-8-H5_S145_L001_R1_001.fastq"                        
## [116] "ITS2-2023-7-8-H7_S146_L001_R1_001.fastq"                        
## [117] "ITS2-2023-8-4-H2_S147_L001_R1_001.fastq"                        
## [118] "ITS2-2023-8-4-H5_S148_L001_R1_001.fastq"                        
## [119] "ITS2-2023-8-4-H6_S149_L001_R1_001.fastq"                        
## [120] "ITS2-2023-8-4-H7_S150_L001_R1_001.fastq"                        
## [121] "ITS2-2023-8-4-H8_S151_L001_R1_001.fastq"                        
## [122] "ITS2-2023-8-4-H9_S152_L001_R1_001.fastq"                        
## [123] "ITS2-Ba001_S153_L001_R1_001.fastq"                              
## [124] "ITS2-Ba002_S154_L001_R1_001.fastq"                              
## [125] "ITS2-Ba003_S155_L001_R1_001.fastq"                              
## [126] "ITS2-Bb001_S156_L001_R1_001.fastq"                              
## [127] "ITS2-Bb002_S157_L001_R1_001.fastq"                              
## [128] "ITS2-Bb003_S158_L001_R1_001.fastq"                              
## [129] "ITS2-Bb004_S159_L001_R1_001.fastq"                              
## [130] "ITS2-Bb005_S160_L001_R1_001.fastq"                              
## [131] "ITS2-Bb007_S161_L001_R1_001.fastq"                              
## [132] "ITS2-Bb008_S162_L001_R1_001.fastq"                              
## [133] "ITS2-Bb009_S163_L001_R1_001.fastq"                              
## [134] "ITS2-Bb010_S164_L001_R1_001.fastq"                              
## [135] "ITS2-Bb011_S165_L001_R1_001.fastq"                              
## [136] "ITS2-Bb012_S166_L001_R1_001.fastq"                              
## [137] "ITS2-Bb013_S167_L001_R1_001.fastq"                              
## [138] "ITS2-Bb014_S168_L001_R1_001.fastq"                              
## [139] "ITS2-Bb015_S169_L001_R1_001.fastq"                              
## [140] "ITS2-Bb016_S170_L001_R1_001.fastq"                              
## [141] "ITS2-Bb017_S171_L001_R1_001.fastq"                              
## [142] "ITS2-Bb018_S172_L001_R1_001.fastq"                              
## [143] "ITS2-Bb019_S173_L001_R1_001.fastq"                              
## [144] "ITS2-Bb020_S174_L001_R1_001.fastq"                              
## [145] "ITS2-Bb021_S175_L001_R1_001.fastq"                              
## [146] "ITS2-Bb022_S176_L001_R1_001.fastq"                              
## [147] "ITS2-Bb023_S177_L001_R1_001.fastq"                              
## [148] "ITS2-Bb024_S178_L001_R1_001.fastq"                              
## [149] "ITS2-Bb025_S179_L001_R1_001.fastq"                              
## [150] "ITS2-Bf001_S180_L001_R1_001.fastq"                              
## [151] "ITS2-Bf002_S181_L001_R1_001.fastq"                              
## [152] "ITS2-Bf003_S182_L001_R1_001.fastq"                              
## [153] "ITS2-Bf004_S183_L001_R1_001.fastq"                              
## [154] "ITS2-Bg001_S184_L001_R1_001.fastq"                              
## [155] "ITS2-Bg002_S185_L001_R1_001.fastq"                              
## [156] "ITS2-Bg003_S186_L001_R1_001.fastq"                              
## [157] "ITS2-Bg004_S187_L001_R1_001.fastq"                              
## [158] "ITS2-Bg005_S188_L001_R1_001.fastq"                              
## [159] "ITS2-Bg006_S189_L001_R1_001.fastq"                              
## [160] "ITS2-Bg007_S190_L001_R1_001.fastq"                              
## [161] "ITS2-Bg008_S191_L001_R1_001.fastq"                              
## [162] "ITS2-Bg009_S192_L001_R1_001.fastq"                              
## [163] "ITS2-Bg010_S193_L001_R1_001.fastq"                              
## [164] "ITS2-Bg011_S194_L001_R1_001.fastq"                              
## [165] "ITS2-Bg012_S195_L001_R1_001.fastq"                              
## [166] "ITS2-Bg013_S196_L001_R1_001.fastq"                              
## [167] "ITS2-Bg014_S197_L001_R1_001.fastq"                              
## [168] "ITS2-Bg015_S198_L001_R1_001.fastq"                              
## [169] "ITS2-Bg016_S199_L001_R1_001.fastq"                              
## [170] "ITS2-Bg017_S200_L001_R1_001.fastq"                              
## [171] "ITS2-Bg018_S201_L001_R1_001.fastq"                              
## [172] "ITS2-Bg019_S202_L001_R1_001.fastq"                              
## [173] "ITS2-Bi001_S203_L001_R1_001.fastq"                              
## [174] "ITS2-Bi002_S204_L001_R1_001.fastq"                              
## [175] "ITS2-Bi003_S205_L001_R1_001.fastq"                              
## [176] "ITS2-Bi004_S206_L001_R1_001.fastq"                              
## [177] "ITS2-Bi005_S207_L001_R1_001.fastq"                              
## [178] "ITS2-Bi006_S208_L001_R1_001.fastq"                              
## [179] "ITS2-Bi007_S209_L001_R1_001.fastq"                              
## [180] "ITS2-CKC0001_S210_L001_R1_001.fastq"                            
## [181] "ITS2-ESE0004_S211_L001_R1_001.fastq"                            
## [182] "ITS2-ext-neg-ctrl-20230909_S212_L001_R1_001.fastq"              
## [183] "ITS2-ext-neg-ctrl-20230923_S213_L001_R1_001.fastq"              
## [184] "ITS2-ext-neg-ctrl-20230924_S214_L001_R1_001.fastq"              
## [185] "ITS2-ext-neg-ctrl-20231007_S215_L001_R1_001.fastq"              
## [186] "ITS2-ext-neg-ctrl-20231008_S216_L001_R1_001.fastq"              
## [187] "ITS2-ext-neg-ctrl-20231009_S217_L001_R1_001.fastq"              
## [188] "ITS2-ext-neg-ctrl-2024220A_S218_L001_R1_001.fastq"              
## [189] "ITS2-ext-neg-ctrl-2024220B_S219_L001_R1_001.fastq"              
## [190] "ITS2-ext-neg-ctrl-2024221A_S220_L001_R1_001.fastq"              
## [191] "ITS2-ext-neg-ctrl-2024221B_S221_L001_R1_001.fastq"              
## [192] "ITS2-ext-neg-ctrl-2024222A_S222_L001_R1_001.fastq"              
## [193] "ITS2-ext-neg-ctrl-2024222B_S223_L001_R1_001.fastq"              
## [194] "ITS2-ext-neg-ctrl-2024312A_S224_L001_R1_001.fastq"              
## [195] "ITS2-ext-neg-ctrl-2024312B_S225_L001_R1_001.fastq"              
## [196] "ITS2-ext-neg-ctrl-2024314A_S226_L001_R1_001.fastq"              
## [197] "ITS2-ext-neg-ctrl-2024314B_S227_L001_R1_001.fastq"              
## [198] "ITS2-ext-neg-ctrl-2024319_S228_L001_R1_001.fastq"               
## [199] "ITS2-ext-neg-ctrl-2024320_S229_L001_R1_001.fastq"               
## [200] "ITS2-KLS0007_S230_L001_R1_001.fastq"                            
## [201] "ITS2-KLS0027_S232_L001_R1_001.fastq"                            
## [202] "ITS2-KLS0044_S233_L001_R1_001.fastq"                            
## [203] "ITS2-KLS0045_S234_L001_R1_001.fastq"                            
## [204] "ITS2-KLS0052_S235_L001_R1_001.fastq"                            
## [205] "ITS2-KLS0054_S236_L001_R1_001.fastq"                            
## [206] "ITS2-KLS0055_S237_L001_R1_001.fastq"                            
## [207] "ITS2-KLS0071_S238_L001_R1_001.fastq"                            
## [208] "ITS2-KLS0095_S239_L001_R1_001.fastq"                            
## [209] "ITS2-KLS0096_S240_L001_R1_001.fastq"                            
## [210] "ITS2-KLS0105_S241_L001_R1_001.fastq"                            
## [211] "ITS2-KLS0106_S242_L001_R1_001.fastq"                            
## [212] "ITS2-KLS0119_S243_L001_R1_001.fastq"                            
## [213] "ITS2-KLS0134_S244_L001_R1_001.fastq"                            
## [214] "ITS2-KLS0135_S245_L001_R1_001.fastq"                            
## [215] "ITS2-KLS0136_S246_L001_R1_001.fastq"                            
## [216] "ITS2-KLS0137_S247_L001_R1_001.fastq"                            
## [217] "ITS2-KLS0138_S248_L001_R1_001.fastq"                            
## [218] "ITS2-KLS0139_S249_L001_R1_001.fastq"                            
## [219] "ITS2-KLS0150_S250_L001_R1_001.fastq"                            
## [220] "ITS2-KLS0153_S251_L001_R1_001.fastq"                            
## [221] "ITS2-KLS0155_S252_L001_R1_001.fastq"                            
## [222] "ITS2-KLS0156_S253_L001_R1_001.fastq"                            
## [223] "ITS2-KLS0159_S254_L001_R1_001.fastq"                            
## [224] "ITS2-KLS0163_S255_L001_R1_001.fastq"                            
## [225] "ITS2-KLS0165_S256_L001_R1_001.fastq"                            
## [226] "ITS2-KLS0167_S257_L001_R1_001.fastq"                            
## [227] "ITS2-KLS0168_S258_L001_R1_001.fastq"                            
## [228] "ITS2-KLS0169_S259_L001_R1_001.fastq"                            
## [229] "ITS2-KLS0170_S260_L001_R1_001.fastq"                            
## [230] "ITS2-KLS0200_S261_L001_R1_001.fastq"                            
## [231] "ITS2-KLS0201_S262_L001_R1_001.fastq"                            
## [232] "ITS2-KLS0205_S263_L001_R1_001.fastq"                            
## [233] "ITS2-KLS0209_S264_L001_R1_001.fastq"                            
## [234] "ITS2-KLS0221_S265_L001_R1_001.fastq"                            
## [235] "ITS2-KLS0224_S266_L001_R1_001.fastq"                            
## [236] "ITS2-KLS0225_S267_L001_R1_001.fastq"                            
## [237] "ITS2-KLS0227_S268_L001_R1_001.fastq"                            
## [238] "ITS2-KLS0241_S269_L001_R1_001.fastq"                            
## [239] "ITS2-KLS0244_S270_L001_R1_001.fastq"                            
## [240] "ITS2-KLS0246_S271_L001_R1_001.fastq"                            
## [241] "ITS2-KLS0248_S272_L001_R1_001.fastq"                            
## [242] "ITS2-KLS0253_S273_L001_R1_001.fastq"                            
## [243] "ITS2-KLS0254_S274_L001_R1_001.fastq"                            
## [244] "ITS2-KLS0256_S231_L001_R1_001.fastq"                            
## [245] "ITS2-KLS0259_S275_L001_R1_001.fastq"                            
## [246] "ITS2-KLS0263_S276_L001_R1_001.fastq"                            
## [247] "ITS2-KLS0266_S277_L001_R1_001.fastq"                            
## [248] "ITS2-KLS0272_S278_L001_R1_001.fastq"                            
## [249] "ITS2-pcr-its2-neg-ctrl-20231021-20231119_S279_L001_R1_001.fastq"
## [250] "ITS2-pcr-its2-neg-ctrl-20231022-20231120_S280_L001_R1_001.fastq"
## [251] "ITS2-pcr-its2-neg-ctrl-20231023_S281_L001_R1_001.fastq"         
## [252] "ITS2-pcr-its2-neg-ctrl-20240411_S282_L001_R1_001.fastq"         
## [253] "ITS2-pcr-its2-neg-ctrl-20240416_S283_L001_R1_001.fastq"         
## [254] "ITS2-pcr-its2-neg-ctrl-20240417_S284_L001_R1_001.fastq"         
## [255] "ITS2-pcr-its2-neg-ctrl-20240418A_S285_L001_R1_001.fastq"        
## [256] "ITS2-pcr-its2-neg-ctrl-20240418B_S286_L001_R1_001.fastq"        
## [257] "ITS2-pcr-its2-neg-ctrl-20240517_S287_L001_R1_001.fastq"         
## [258] "ITS2-pcr-its2-neg-ctrl-20240524_S288_L001_R1_001.fastq"         
## [259] "ITS2-pcr-its2-neg-ctrl-Saskia-20240411_S289_L001_R1_001.fastq"  
## [260] "ITS2-SCA0009_S290_L001_R1_001.fastq"                            
## [261] "ITS2-SCA0010_S291_L001_R1_001.fastq"                            
## [262] "ITS2-SCA0013_S292_L001_R1_001.fastq"
                                  strsplit(rownames(as.data.frame(out)),  "_S")
## [[1]]
## [1] "ITS2-2020-6-16-H1"    "31_L001_R1_001.fastq"
## 
## [[2]]
## [1] "ITS2-2020-6-16-H5"    "32_L001_R1_001.fastq"
## 
## [[3]]
## [1] "ITS2-2020-6-16-H6"    "33_L001_R1_001.fastq"
## 
## [[4]]
## [1] "ITS2-2020-6-17-H2"    "34_L001_R1_001.fastq"
## 
## [[5]]
## [1] "ITS2-2020-6-17-H4"    "35_L001_R1_001.fastq"
## 
## [[6]]
## [1] "ITS2-2020-6-17-H8"    "36_L001_R1_001.fastq"
## 
## [[7]]
## [1] "ITS2-2020-6-18-H3"    "37_L001_R1_001.fastq"
## 
## [[8]]
## [1] "ITS2-2020-6-18-H7"    "38_L001_R1_001.fastq"
## 
## [[9]]
## [1] "ITS2-2020-6-18-H9"    "39_L001_R1_001.fastq"
## 
## [[10]]
## [1] "ITS2-2020-6-3-H1"     "40_L001_R1_001.fastq"
## 
## [[11]]
## [1] "ITS2-2020-6-3-H5"     "41_L001_R1_001.fastq"
## 
## [[12]]
## [1] "ITS2-2020-6-3-H6"     "42_L001_R1_001.fastq"
## 
## [[13]]
## [1] "ITS2-2020-6-30-H1"    "43_L001_R1_001.fastq"
## 
## [[14]]
## [1] "ITS2-2020-6-30-H5"    "44_L001_R1_001.fastq"
## 
## [[15]]
## [1] "ITS2-2020-6-30-H6"    "45_L001_R1_001.fastq"
## 
## [[16]]
## [1] "ITS2-2020-6-4-H2"     "46_L001_R1_001.fastq"
## 
## [[17]]
## [1] "ITS2-2020-6-4-H4"     "47_L001_R1_001.fastq"
## 
## [[18]]
## [1] "ITS2-2020-6-4-H8"     "48_L001_R1_001.fastq"
## 
## [[19]]
## [1] "ITS2-2020-6-5-H3"     "49_L001_R1_001.fastq"
## 
## [[20]]
## [1] "ITS2-2020-6-5-H7"     "50_L001_R1_001.fastq"
## 
## [[21]]
## [1] "ITS2-2020-6-5-H9"     "51_L001_R1_001.fastq"
## 
## [[22]]
## [1] "ITS2-2020-7-1-H2"     "52_L001_R1_001.fastq"
## 
## [[23]]
## [1] "ITS2-2020-7-1-H4"     "53_L001_R1_001.fastq"
## 
## [[24]]
## [1] "ITS2-2020-7-1-H8"     "54_L001_R1_001.fastq"
## 
## [[25]]
## [1] "ITS2-2020-7-14-H1"    "55_L001_R1_001.fastq"
## 
## [[26]]
## [1] "ITS2-2020-7-14-H5"    "56_L001_R1_001.fastq"
## 
## [[27]]
## [1] "ITS2-2020-7-14-H6"    "57_L001_R1_001.fastq"
## 
## [[28]]
## [1] "ITS2-2020-7-15-H2"    "58_L001_R1_001.fastq"
## 
## [[29]]
## [1] "ITS2-2020-7-15-H4"    "59_L001_R1_001.fastq"
## 
## [[30]]
## [1] "ITS2-2020-7-15-H8"    "60_L001_R1_001.fastq"
## 
## [[31]]
## [1] "ITS2-2020-7-16-H3"    "61_L001_R1_001.fastq"
## 
## [[32]]
## [1] "ITS2-2020-7-16-H7"    "62_L001_R1_001.fastq"
## 
## [[33]]
## [1] "ITS2-2020-7-16-H9"    "63_L001_R1_001.fastq"
## 
## [[34]]
## [1] "ITS2-2020-7-2-H3"     "64_L001_R1_001.fastq"
## 
## [[35]]
## [1] "ITS2-2020-7-2-H7"     "65_L001_R1_001.fastq"
## 
## [[36]]
## [1] "ITS2-2020-7-2-H9"     "66_L001_R1_001.fastq"
## 
## [[37]]
## [1] "ITS2-2021-6-13-H1"    "67_L001_R1_001.fastq"
## 
## [[38]]
## [1] "ITS2-2021-6-13-H3"    "68_L001_R1_001.fastq"
## 
## [[39]]
## [1] "ITS2-2021-6-14-H11"   "69_L001_R1_001.fastq"
## 
## [[40]]
## [1] "ITS2-2021-6-14-H6"    "70_L001_R1_001.fastq"
## 
## [[41]]
## [1] "ITS2-2021-6-14-H7"    "71_L001_R1_001.fastq"
## 
## [[42]]
## [1] "ITS2-2021-6-15-H8"    "72_L001_R1_001.fastq"
## 
## [[43]]
## [1] "ITS2-2021-6-21-H10"   "73_L001_R1_001.fastq"
## 
## [[44]]
## [1] "ITS2-2021-6-21-H12"   "74_L001_R1_001.fastq"
## 
## [[45]]
## [1] "ITS2-2021-6-21-H9"    "75_L001_R1_001.fastq"
## 
## [[46]]
## [1] "ITS2-2021-6-27-H21"   "76_L001_R1_001.fastq"
## 
## [[47]]
## [1] "ITS2-2021-6-27-H22"   "77_L001_R1_001.fastq"
## 
## [[48]]
## [1] "ITS2-2021-6-27-H27"   "78_L001_R1_001.fastq"
## 
## [[49]]
## [1] "ITS2-2021-6-28-H25"   "79_L001_R1_001.fastq"
## 
## [[50]]
## [1] "ITS2-2021-6-28-H26"   "80_L001_R1_001.fastq"
## 
## [[51]]
## [1] "ITS2-2021-6-28-H28"   "81_L001_R1_001.fastq"
## 
## [[52]]
## [1] "ITS2-2021-6-29-H17"   "82_L001_R1_001.fastq"
## 
## [[53]]
## [1] "ITS2-2021-6-29-H23"   "83_L001_R1_001.fastq"
## 
## [[54]]
## [1] "ITS2-2021-6-29-H24"   "84_L001_R1_001.fastq"
## 
## [[55]]
## [1] "ITS2-2021-6-4-H21"    "85_L001_R1_001.fastq"
## 
## [[56]]
## [1] "ITS2-2021-6-4-H22"    "86_L001_R1_001.fastq"
## 
## [[57]]
## [1] "ITS2-2021-6-4-H27"    "87_L001_R1_001.fastq"
## 
## [[58]]
## [1] "ITS2-2021-6-5-H18"    "88_L001_R1_001.fastq"
## 
## [[59]]
## [1] "ITS2-2021-6-5-H25"    "89_L001_R1_001.fastq"
## 
## [[60]]
## [1] "ITS2-2021-6-5-H26"    "90_L001_R1_001.fastq"
## 
## [[61]]
## [1] "ITS2-2021-6-6-H17"    "91_L001_R1_001.fastq"
## 
## [[62]]
## [1] "ITS2-2021-6-6-H24"    "92_L001_R1_001.fastq"
## 
## [[63]]
## [1] "ITS2-2021-6-7-H23"    "93_L001_R1_001.fastq"
## 
## [[64]]
## [1] "ITS2-2021-7-14-H10"   "94_L001_R1_001.fastq"
## 
## [[65]]
## [1] "ITS2-2021-7-14-H12"   "95_L001_R1_001.fastq"
## 
## [[66]]
## [1] "ITS2-2021-7-20-H27"   "96_L001_R1_001.fastq"
## 
## [[67]]
## [1] "ITS2-2021-7-21-H25"   "97_L001_R1_001.fastq"
## 
## [[68]]
## [1] "ITS2-2021-7-21-H26"   "98_L001_R1_001.fastq"
## 
## [[69]]
## [1] "ITS2-2021-7-21-H28"   "99_L001_R1_001.fastq"
## 
## [[70]]
## [1] "ITS2-2021-7-6-H11"     "100_L001_R1_001.fastq"
## 
## [[71]]
## [1] "ITS2-2021-7-6-H30"     "101_L001_R1_001.fastq"
## 
## [[72]]
## [1] "ITS2-2021-7-6-H6"      "102_L001_R1_001.fastq"
## 
## [[73]]
## [1] "ITS2-2021-7-7-H4"      "103_L001_R1_001.fastq"
## 
## [[74]]
## [1] "ITS2-2021-7-7-H8"      "104_L001_R1_001.fastq"
## 
## [[75]]
## [1] "ITS2-2021-7-8-H3"      "105_L001_R1_001.fastq"
## 
## [[76]]
## [1] "ITS2-2023-6-12-H3"     "106_L001_R1_001.fastq"
## 
## [[77]]
## [1] "ITS2-2023-6-12-H5"     "107_L001_R1_001.fastq"
## 
## [[78]]
## [1] "ITS2-2023-6-12-H7"     "108_L001_R1_001.fastq"
## 
## [[79]]
## [1] "ITS2-2023-6-13-H6"     "109_L001_R1_001.fastq"
## 
## [[80]]
## [1] "ITS2-2023-6-13-H8"     "110_L001_R1_001.fastq"
## 
## [[81]]
## [1] "ITS2-2023-6-13-H9"     "111_L001_R1_001.fastq"
## 
## [[82]]
## [1] "ITS2-2023-6-14-H3"     "112_L001_R1_001.fastq"
## 
## [[83]]
## [1] "ITS2-2023-6-14-H7"     "113_L001_R1_001.fastq"
## 
## [[84]]
## [1] "ITS2-2023-6-14-H9"     "114_L001_R1_001.fastq"
## 
## [[85]]
## [1] "ITS2-2023-6-16-H5"     "115_L001_R1_001.fastq"
## 
## [[86]]
## [1] "ITS2-2023-6-24-H6"     "116_L001_R1_001.fastq"
## 
## [[87]]
## [1] "ITS2-2023-6-24-H8"     "117_L001_R1_001.fastq"
## 
## [[88]]
## [1] "ITS2-2023-6-25-H2"     "118_L001_R1_001.fastq"
## 
## [[89]]
## [1] "ITS2-2023-6-25-H4"     "119_L001_R1_001.fastq"
## 
## [[90]]
## [1] "ITS2-2023-6-26-H1"     "120_L001_R1_001.fastq"
## 
## [[91]]
## [1] "ITS2-2023-6-26-H7"     "121_L001_R1_001.fastq"
## 
## [[92]]
## [1] "ITS2-2023-6-27-H3"     "122_L001_R1_001.fastq"
## 
## [[93]]
## [1] "ITS2-2023-6-27-H5"     "123_L001_R1_001.fastq"
## 
## [[94]]
## [1] "ITS2-2023-6-8-H1"      "124_L001_R1_001.fastq"
## 
## [[95]]
## [1] "ITS2-2023-6-8-H2"      "125_L001_R1_001.fastq"
## 
## [[96]]
## [1] "ITS2-2023-6-8-H4"      "126_L001_R1_001.fastq"
## 
## [[97]]
## [1] "ITS2-2023-6-9-H2"      "127_L001_R1_001.fastq"
## 
## [[98]]
## [1] "ITS2-2023-6-9-H4"      "128_L001_R1_001.fastq"
## 
## [[99]]
## [1] "ITS2-2023-7-15-H6"     "129_L001_R1_001.fastq"
## 
## [[100]]
## [1] "ITS2-2023-7-16-H4"     "130_L001_R1_001.fastq"
## 
## [[101]]
## [1] "ITS2-2023-7-17-H1"     "131_L001_R1_001.fastq"
## 
## [[102]]
## [1] "ITS2-2023-7-18-H3"     "132_L001_R1_001.fastq"
## 
## [[103]]
## [1] "ITS2-2023-7-18-H7"     "133_L001_R1_001.fastq"
## 
## [[104]]
## [1] "ITS2-2023-7-29-H5"     "134_L001_R1_001.fastq"
## 
## [[105]]
## [1] "ITS2-2023-7-29-H7"     "135_L001_R1_001.fastq"
## 
## [[106]]
## [1] "ITS2-2023-7-30-H8"     "136_L001_R1_001.fastq"
## 
## [[107]]
## [1] "ITS2-2023-7-30-H9"     "137_L001_R1_001.fastq"
## 
## [[108]]
## [1] "ITS2-2023-7-5-H1"      "138_L001_R1_001.fastq"
## 
## [[109]]
## [1] "ITS2-2023-7-5-H2"      "139_L001_R1_001.fastq"
## 
## [[110]]
## [1] "ITS2-2023-7-5-H4"      "140_L001_R1_001.fastq"
## 
## [[111]]
## [1] "ITS2-2023-7-6-H6"      "141_L001_R1_001.fastq"
## 
## [[112]]
## [1] "ITS2-2023-7-6-H8"      "142_L001_R1_001.fastq"
## 
## [[113]]
## [1] "ITS2-2023-7-6-H9"      "143_L001_R1_001.fastq"
## 
## [[114]]
## [1] "ITS2-2023-7-8-H3"      "144_L001_R1_001.fastq"
## 
## [[115]]
## [1] "ITS2-2023-7-8-H5"      "145_L001_R1_001.fastq"
## 
## [[116]]
## [1] "ITS2-2023-7-8-H7"      "146_L001_R1_001.fastq"
## 
## [[117]]
## [1] "ITS2-2023-8-4-H2"      "147_L001_R1_001.fastq"
## 
## [[118]]
## [1] "ITS2-2023-8-4-H5"      "148_L001_R1_001.fastq"
## 
## [[119]]
## [1] "ITS2-2023-8-4-H6"      "149_L001_R1_001.fastq"
## 
## [[120]]
## [1] "ITS2-2023-8-4-H7"      "150_L001_R1_001.fastq"
## 
## [[121]]
## [1] "ITS2-2023-8-4-H8"      "151_L001_R1_001.fastq"
## 
## [[122]]
## [1] "ITS2-2023-8-4-H9"      "152_L001_R1_001.fastq"
## 
## [[123]]
## [1] "ITS2-Ba001"            "153_L001_R1_001.fastq"
## 
## [[124]]
## [1] "ITS2-Ba002"            "154_L001_R1_001.fastq"
## 
## [[125]]
## [1] "ITS2-Ba003"            "155_L001_R1_001.fastq"
## 
## [[126]]
## [1] "ITS2-Bb001"            "156_L001_R1_001.fastq"
## 
## [[127]]
## [1] "ITS2-Bb002"            "157_L001_R1_001.fastq"
## 
## [[128]]
## [1] "ITS2-Bb003"            "158_L001_R1_001.fastq"
## 
## [[129]]
## [1] "ITS2-Bb004"            "159_L001_R1_001.fastq"
## 
## [[130]]
## [1] "ITS2-Bb005"            "160_L001_R1_001.fastq"
## 
## [[131]]
## [1] "ITS2-Bb007"            "161_L001_R1_001.fastq"
## 
## [[132]]
## [1] "ITS2-Bb008"            "162_L001_R1_001.fastq"
## 
## [[133]]
## [1] "ITS2-Bb009"            "163_L001_R1_001.fastq"
## 
## [[134]]
## [1] "ITS2-Bb010"            "164_L001_R1_001.fastq"
## 
## [[135]]
## [1] "ITS2-Bb011"            "165_L001_R1_001.fastq"
## 
## [[136]]
## [1] "ITS2-Bb012"            "166_L001_R1_001.fastq"
## 
## [[137]]
## [1] "ITS2-Bb013"            "167_L001_R1_001.fastq"
## 
## [[138]]
## [1] "ITS2-Bb014"            "168_L001_R1_001.fastq"
## 
## [[139]]
## [1] "ITS2-Bb015"            "169_L001_R1_001.fastq"
## 
## [[140]]
## [1] "ITS2-Bb016"            "170_L001_R1_001.fastq"
## 
## [[141]]
## [1] "ITS2-Bb017"            "171_L001_R1_001.fastq"
## 
## [[142]]
## [1] "ITS2-Bb018"            "172_L001_R1_001.fastq"
## 
## [[143]]
## [1] "ITS2-Bb019"            "173_L001_R1_001.fastq"
## 
## [[144]]
## [1] "ITS2-Bb020"            "174_L001_R1_001.fastq"
## 
## [[145]]
## [1] "ITS2-Bb021"            "175_L001_R1_001.fastq"
## 
## [[146]]
## [1] "ITS2-Bb022"            "176_L001_R1_001.fastq"
## 
## [[147]]
## [1] "ITS2-Bb023"            "177_L001_R1_001.fastq"
## 
## [[148]]
## [1] "ITS2-Bb024"            "178_L001_R1_001.fastq"
## 
## [[149]]
## [1] "ITS2-Bb025"            "179_L001_R1_001.fastq"
## 
## [[150]]
## [1] "ITS2-Bf001"            "180_L001_R1_001.fastq"
## 
## [[151]]
## [1] "ITS2-Bf002"            "181_L001_R1_001.fastq"
## 
## [[152]]
## [1] "ITS2-Bf003"            "182_L001_R1_001.fastq"
## 
## [[153]]
## [1] "ITS2-Bf004"            "183_L001_R1_001.fastq"
## 
## [[154]]
## [1] "ITS2-Bg001"            "184_L001_R1_001.fastq"
## 
## [[155]]
## [1] "ITS2-Bg002"            "185_L001_R1_001.fastq"
## 
## [[156]]
## [1] "ITS2-Bg003"            "186_L001_R1_001.fastq"
## 
## [[157]]
## [1] "ITS2-Bg004"            "187_L001_R1_001.fastq"
## 
## [[158]]
## [1] "ITS2-Bg005"            "188_L001_R1_001.fastq"
## 
## [[159]]
## [1] "ITS2-Bg006"            "189_L001_R1_001.fastq"
## 
## [[160]]
## [1] "ITS2-Bg007"            "190_L001_R1_001.fastq"
## 
## [[161]]
## [1] "ITS2-Bg008"            "191_L001_R1_001.fastq"
## 
## [[162]]
## [1] "ITS2-Bg009"            "192_L001_R1_001.fastq"
## 
## [[163]]
## [1] "ITS2-Bg010"            "193_L001_R1_001.fastq"
## 
## [[164]]
## [1] "ITS2-Bg011"            "194_L001_R1_001.fastq"
## 
## [[165]]
## [1] "ITS2-Bg012"            "195_L001_R1_001.fastq"
## 
## [[166]]
## [1] "ITS2-Bg013"            "196_L001_R1_001.fastq"
## 
## [[167]]
## [1] "ITS2-Bg014"            "197_L001_R1_001.fastq"
## 
## [[168]]
## [1] "ITS2-Bg015"            "198_L001_R1_001.fastq"
## 
## [[169]]
## [1] "ITS2-Bg016"            "199_L001_R1_001.fastq"
## 
## [[170]]
## [1] "ITS2-Bg017"            "200_L001_R1_001.fastq"
## 
## [[171]]
## [1] "ITS2-Bg018"            "201_L001_R1_001.fastq"
## 
## [[172]]
## [1] "ITS2-Bg019"            "202_L001_R1_001.fastq"
## 
## [[173]]
## [1] "ITS2-Bi001"            "203_L001_R1_001.fastq"
## 
## [[174]]
## [1] "ITS2-Bi002"            "204_L001_R1_001.fastq"
## 
## [[175]]
## [1] "ITS2-Bi003"            "205_L001_R1_001.fastq"
## 
## [[176]]
## [1] "ITS2-Bi004"            "206_L001_R1_001.fastq"
## 
## [[177]]
## [1] "ITS2-Bi005"            "207_L001_R1_001.fastq"
## 
## [[178]]
## [1] "ITS2-Bi006"            "208_L001_R1_001.fastq"
## 
## [[179]]
## [1] "ITS2-Bi007"            "209_L001_R1_001.fastq"
## 
## [[180]]
## [1] "ITS2-CKC0001"          "210_L001_R1_001.fastq"
## 
## [[181]]
## [1] "ITS2-ESE0004"          "211_L001_R1_001.fastq"
## 
## [[182]]
## [1] "ITS2-ext-neg-ctrl-20230909" "212_L001_R1_001.fastq"     
## 
## [[183]]
## [1] "ITS2-ext-neg-ctrl-20230923" "213_L001_R1_001.fastq"     
## 
## [[184]]
## [1] "ITS2-ext-neg-ctrl-20230924" "214_L001_R1_001.fastq"     
## 
## [[185]]
## [1] "ITS2-ext-neg-ctrl-20231007" "215_L001_R1_001.fastq"     
## 
## [[186]]
## [1] "ITS2-ext-neg-ctrl-20231008" "216_L001_R1_001.fastq"     
## 
## [[187]]
## [1] "ITS2-ext-neg-ctrl-20231009" "217_L001_R1_001.fastq"     
## 
## [[188]]
## [1] "ITS2-ext-neg-ctrl-2024220A" "218_L001_R1_001.fastq"     
## 
## [[189]]
## [1] "ITS2-ext-neg-ctrl-2024220B" "219_L001_R1_001.fastq"     
## 
## [[190]]
## [1] "ITS2-ext-neg-ctrl-2024221A" "220_L001_R1_001.fastq"     
## 
## [[191]]
## [1] "ITS2-ext-neg-ctrl-2024221B" "221_L001_R1_001.fastq"     
## 
## [[192]]
## [1] "ITS2-ext-neg-ctrl-2024222A" "222_L001_R1_001.fastq"     
## 
## [[193]]
## [1] "ITS2-ext-neg-ctrl-2024222B" "223_L001_R1_001.fastq"     
## 
## [[194]]
## [1] "ITS2-ext-neg-ctrl-2024312A" "224_L001_R1_001.fastq"     
## 
## [[195]]
## [1] "ITS2-ext-neg-ctrl-2024312B" "225_L001_R1_001.fastq"     
## 
## [[196]]
## [1] "ITS2-ext-neg-ctrl-2024314A" "226_L001_R1_001.fastq"     
## 
## [[197]]
## [1] "ITS2-ext-neg-ctrl-2024314B" "227_L001_R1_001.fastq"     
## 
## [[198]]
## [1] "ITS2-ext-neg-ctrl-2024319" "228_L001_R1_001.fastq"    
## 
## [[199]]
## [1] "ITS2-ext-neg-ctrl-2024320" "229_L001_R1_001.fastq"    
## 
## [[200]]
## [1] "ITS2-KLS0007"          "230_L001_R1_001.fastq"
## 
## [[201]]
## [1] "ITS2-KLS0027"          "232_L001_R1_001.fastq"
## 
## [[202]]
## [1] "ITS2-KLS0044"          "233_L001_R1_001.fastq"
## 
## [[203]]
## [1] "ITS2-KLS0045"          "234_L001_R1_001.fastq"
## 
## [[204]]
## [1] "ITS2-KLS0052"          "235_L001_R1_001.fastq"
## 
## [[205]]
## [1] "ITS2-KLS0054"          "236_L001_R1_001.fastq"
## 
## [[206]]
## [1] "ITS2-KLS0055"          "237_L001_R1_001.fastq"
## 
## [[207]]
## [1] "ITS2-KLS0071"          "238_L001_R1_001.fastq"
## 
## [[208]]
## [1] "ITS2-KLS0095"          "239_L001_R1_001.fastq"
## 
## [[209]]
## [1] "ITS2-KLS0096"          "240_L001_R1_001.fastq"
## 
## [[210]]
## [1] "ITS2-KLS0105"          "241_L001_R1_001.fastq"
## 
## [[211]]
## [1] "ITS2-KLS0106"          "242_L001_R1_001.fastq"
## 
## [[212]]
## [1] "ITS2-KLS0119"          "243_L001_R1_001.fastq"
## 
## [[213]]
## [1] "ITS2-KLS0134"          "244_L001_R1_001.fastq"
## 
## [[214]]
## [1] "ITS2-KLS0135"          "245_L001_R1_001.fastq"
## 
## [[215]]
## [1] "ITS2-KLS0136"          "246_L001_R1_001.fastq"
## 
## [[216]]
## [1] "ITS2-KLS0137"          "247_L001_R1_001.fastq"
## 
## [[217]]
## [1] "ITS2-KLS0138"          "248_L001_R1_001.fastq"
## 
## [[218]]
## [1] "ITS2-KLS0139"          "249_L001_R1_001.fastq"
## 
## [[219]]
## [1] "ITS2-KLS0150"          "250_L001_R1_001.fastq"
## 
## [[220]]
## [1] "ITS2-KLS0153"          "251_L001_R1_001.fastq"
## 
## [[221]]
## [1] "ITS2-KLS0155"          "252_L001_R1_001.fastq"
## 
## [[222]]
## [1] "ITS2-KLS0156"          "253_L001_R1_001.fastq"
## 
## [[223]]
## [1] "ITS2-KLS0159"          "254_L001_R1_001.fastq"
## 
## [[224]]
## [1] "ITS2-KLS0163"          "255_L001_R1_001.fastq"
## 
## [[225]]
## [1] "ITS2-KLS0165"          "256_L001_R1_001.fastq"
## 
## [[226]]
## [1] "ITS2-KLS0167"          "257_L001_R1_001.fastq"
## 
## [[227]]
## [1] "ITS2-KLS0168"          "258_L001_R1_001.fastq"
## 
## [[228]]
## [1] "ITS2-KLS0169"          "259_L001_R1_001.fastq"
## 
## [[229]]
## [1] "ITS2-KLS0170"          "260_L001_R1_001.fastq"
## 
## [[230]]
## [1] "ITS2-KLS0200"          "261_L001_R1_001.fastq"
## 
## [[231]]
## [1] "ITS2-KLS0201"          "262_L001_R1_001.fastq"
## 
## [[232]]
## [1] "ITS2-KLS0205"          "263_L001_R1_001.fastq"
## 
## [[233]]
## [1] "ITS2-KLS0209"          "264_L001_R1_001.fastq"
## 
## [[234]]
## [1] "ITS2-KLS0221"          "265_L001_R1_001.fastq"
## 
## [[235]]
## [1] "ITS2-KLS0224"          "266_L001_R1_001.fastq"
## 
## [[236]]
## [1] "ITS2-KLS0225"          "267_L001_R1_001.fastq"
## 
## [[237]]
## [1] "ITS2-KLS0227"          "268_L001_R1_001.fastq"
## 
## [[238]]
## [1] "ITS2-KLS0241"          "269_L001_R1_001.fastq"
## 
## [[239]]
## [1] "ITS2-KLS0244"          "270_L001_R1_001.fastq"
## 
## [[240]]
## [1] "ITS2-KLS0246"          "271_L001_R1_001.fastq"
## 
## [[241]]
## [1] "ITS2-KLS0248"          "272_L001_R1_001.fastq"
## 
## [[242]]
## [1] "ITS2-KLS0253"          "273_L001_R1_001.fastq"
## 
## [[243]]
## [1] "ITS2-KLS0254"          "274_L001_R1_001.fastq"
## 
## [[244]]
## [1] "ITS2-KLS0256"          "231_L001_R1_001.fastq"
## 
## [[245]]
## [1] "ITS2-KLS0259"          "275_L001_R1_001.fastq"
## 
## [[246]]
## [1] "ITS2-KLS0263"          "276_L001_R1_001.fastq"
## 
## [[247]]
## [1] "ITS2-KLS0266"          "277_L001_R1_001.fastq"
## 
## [[248]]
## [1] "ITS2-KLS0272"          "278_L001_R1_001.fastq"
## 
## [[249]]
## [1] "ITS2-pcr-its2-neg-ctrl-20231021-20231119"
## [2] "279_L001_R1_001.fastq"                   
## 
## [[250]]
## [1] "ITS2-pcr-its2-neg-ctrl-20231022-20231120"
## [2] "280_L001_R1_001.fastq"                   
## 
## [[251]]
## [1] "ITS2-pcr-its2-neg-ctrl-20231023" "281_L001_R1_001.fastq"          
## 
## [[252]]
## [1] "ITS2-pcr-its2-neg-ctrl-20240411" "282_L001_R1_001.fastq"          
## 
## [[253]]
## [1] "ITS2-pcr-its2-neg-ctrl-20240416" "283_L001_R1_001.fastq"          
## 
## [[254]]
## [1] "ITS2-pcr-its2-neg-ctrl-20240417" "284_L001_R1_001.fastq"          
## 
## [[255]]
## [1] "ITS2-pcr-its2-neg-ctrl-20240418A" "285_L001_R1_001.fastq"           
## 
## [[256]]
## [1] "ITS2-pcr-its2-neg-ctrl-20240418B" "286_L001_R1_001.fastq"           
## 
## [[257]]
## [1] "ITS2-pcr-its2-neg-ctrl-20240517" "287_L001_R1_001.fastq"          
## 
## [[258]]
## [1] "ITS2-pcr-its2-neg-ctrl-20240524" "288_L001_R1_001.fastq"          
## 
## [[259]]
## [1] "ITS2-pcr-its2-neg-ctrl-Saskia-20240411"
## [2] "289_L001_R1_001.fastq"                 
## 
## [[260]]
## [1] "ITS2-SCA0009"          "290_L001_R1_001.fastq"
## 
## [[261]]
## [1] "ITS2-SCA0010"          "291_L001_R1_001.fastq"
## 
## [[262]]
## [1] "ITS2-SCA0013"          "292_L001_R1_001.fastq"
                           lapply(strsplit(rownames(as.data.frame(out)),  "_S"), function(l) l[[1]])
## [[1]]
## [1] "ITS2-2020-6-16-H1"
## 
## [[2]]
## [1] "ITS2-2020-6-16-H5"
## 
## [[3]]
## [1] "ITS2-2020-6-16-H6"
## 
## [[4]]
## [1] "ITS2-2020-6-17-H2"
## 
## [[5]]
## [1] "ITS2-2020-6-17-H4"
## 
## [[6]]
## [1] "ITS2-2020-6-17-H8"
## 
## [[7]]
## [1] "ITS2-2020-6-18-H3"
## 
## [[8]]
## [1] "ITS2-2020-6-18-H7"
## 
## [[9]]
## [1] "ITS2-2020-6-18-H9"
## 
## [[10]]
## [1] "ITS2-2020-6-3-H1"
## 
## [[11]]
## [1] "ITS2-2020-6-3-H5"
## 
## [[12]]
## [1] "ITS2-2020-6-3-H6"
## 
## [[13]]
## [1] "ITS2-2020-6-30-H1"
## 
## [[14]]
## [1] "ITS2-2020-6-30-H5"
## 
## [[15]]
## [1] "ITS2-2020-6-30-H6"
## 
## [[16]]
## [1] "ITS2-2020-6-4-H2"
## 
## [[17]]
## [1] "ITS2-2020-6-4-H4"
## 
## [[18]]
## [1] "ITS2-2020-6-4-H8"
## 
## [[19]]
## [1] "ITS2-2020-6-5-H3"
## 
## [[20]]
## [1] "ITS2-2020-6-5-H7"
## 
## [[21]]
## [1] "ITS2-2020-6-5-H9"
## 
## [[22]]
## [1] "ITS2-2020-7-1-H2"
## 
## [[23]]
## [1] "ITS2-2020-7-1-H4"
## 
## [[24]]
## [1] "ITS2-2020-7-1-H8"
## 
## [[25]]
## [1] "ITS2-2020-7-14-H1"
## 
## [[26]]
## [1] "ITS2-2020-7-14-H5"
## 
## [[27]]
## [1] "ITS2-2020-7-14-H6"
## 
## [[28]]
## [1] "ITS2-2020-7-15-H2"
## 
## [[29]]
## [1] "ITS2-2020-7-15-H4"
## 
## [[30]]
## [1] "ITS2-2020-7-15-H8"
## 
## [[31]]
## [1] "ITS2-2020-7-16-H3"
## 
## [[32]]
## [1] "ITS2-2020-7-16-H7"
## 
## [[33]]
## [1] "ITS2-2020-7-16-H9"
## 
## [[34]]
## [1] "ITS2-2020-7-2-H3"
## 
## [[35]]
## [1] "ITS2-2020-7-2-H7"
## 
## [[36]]
## [1] "ITS2-2020-7-2-H9"
## 
## [[37]]
## [1] "ITS2-2021-6-13-H1"
## 
## [[38]]
## [1] "ITS2-2021-6-13-H3"
## 
## [[39]]
## [1] "ITS2-2021-6-14-H11"
## 
## [[40]]
## [1] "ITS2-2021-6-14-H6"
## 
## [[41]]
## [1] "ITS2-2021-6-14-H7"
## 
## [[42]]
## [1] "ITS2-2021-6-15-H8"
## 
## [[43]]
## [1] "ITS2-2021-6-21-H10"
## 
## [[44]]
## [1] "ITS2-2021-6-21-H12"
## 
## [[45]]
## [1] "ITS2-2021-6-21-H9"
## 
## [[46]]
## [1] "ITS2-2021-6-27-H21"
## 
## [[47]]
## [1] "ITS2-2021-6-27-H22"
## 
## [[48]]
## [1] "ITS2-2021-6-27-H27"
## 
## [[49]]
## [1] "ITS2-2021-6-28-H25"
## 
## [[50]]
## [1] "ITS2-2021-6-28-H26"
## 
## [[51]]
## [1] "ITS2-2021-6-28-H28"
## 
## [[52]]
## [1] "ITS2-2021-6-29-H17"
## 
## [[53]]
## [1] "ITS2-2021-6-29-H23"
## 
## [[54]]
## [1] "ITS2-2021-6-29-H24"
## 
## [[55]]
## [1] "ITS2-2021-6-4-H21"
## 
## [[56]]
## [1] "ITS2-2021-6-4-H22"
## 
## [[57]]
## [1] "ITS2-2021-6-4-H27"
## 
## [[58]]
## [1] "ITS2-2021-6-5-H18"
## 
## [[59]]
## [1] "ITS2-2021-6-5-H25"
## 
## [[60]]
## [1] "ITS2-2021-6-5-H26"
## 
## [[61]]
## [1] "ITS2-2021-6-6-H17"
## 
## [[62]]
## [1] "ITS2-2021-6-6-H24"
## 
## [[63]]
## [1] "ITS2-2021-6-7-H23"
## 
## [[64]]
## [1] "ITS2-2021-7-14-H10"
## 
## [[65]]
## [1] "ITS2-2021-7-14-H12"
## 
## [[66]]
## [1] "ITS2-2021-7-20-H27"
## 
## [[67]]
## [1] "ITS2-2021-7-21-H25"
## 
## [[68]]
## [1] "ITS2-2021-7-21-H26"
## 
## [[69]]
## [1] "ITS2-2021-7-21-H28"
## 
## [[70]]
## [1] "ITS2-2021-7-6-H11"
## 
## [[71]]
## [1] "ITS2-2021-7-6-H30"
## 
## [[72]]
## [1] "ITS2-2021-7-6-H6"
## 
## [[73]]
## [1] "ITS2-2021-7-7-H4"
## 
## [[74]]
## [1] "ITS2-2021-7-7-H8"
## 
## [[75]]
## [1] "ITS2-2021-7-8-H3"
## 
## [[76]]
## [1] "ITS2-2023-6-12-H3"
## 
## [[77]]
## [1] "ITS2-2023-6-12-H5"
## 
## [[78]]
## [1] "ITS2-2023-6-12-H7"
## 
## [[79]]
## [1] "ITS2-2023-6-13-H6"
## 
## [[80]]
## [1] "ITS2-2023-6-13-H8"
## 
## [[81]]
## [1] "ITS2-2023-6-13-H9"
## 
## [[82]]
## [1] "ITS2-2023-6-14-H3"
## 
## [[83]]
## [1] "ITS2-2023-6-14-H7"
## 
## [[84]]
## [1] "ITS2-2023-6-14-H9"
## 
## [[85]]
## [1] "ITS2-2023-6-16-H5"
## 
## [[86]]
## [1] "ITS2-2023-6-24-H6"
## 
## [[87]]
## [1] "ITS2-2023-6-24-H8"
## 
## [[88]]
## [1] "ITS2-2023-6-25-H2"
## 
## [[89]]
## [1] "ITS2-2023-6-25-H4"
## 
## [[90]]
## [1] "ITS2-2023-6-26-H1"
## 
## [[91]]
## [1] "ITS2-2023-6-26-H7"
## 
## [[92]]
## [1] "ITS2-2023-6-27-H3"
## 
## [[93]]
## [1] "ITS2-2023-6-27-H5"
## 
## [[94]]
## [1] "ITS2-2023-6-8-H1"
## 
## [[95]]
## [1] "ITS2-2023-6-8-H2"
## 
## [[96]]
## [1] "ITS2-2023-6-8-H4"
## 
## [[97]]
## [1] "ITS2-2023-6-9-H2"
## 
## [[98]]
## [1] "ITS2-2023-6-9-H4"
## 
## [[99]]
## [1] "ITS2-2023-7-15-H6"
## 
## [[100]]
## [1] "ITS2-2023-7-16-H4"
## 
## [[101]]
## [1] "ITS2-2023-7-17-H1"
## 
## [[102]]
## [1] "ITS2-2023-7-18-H3"
## 
## [[103]]
## [1] "ITS2-2023-7-18-H7"
## 
## [[104]]
## [1] "ITS2-2023-7-29-H5"
## 
## [[105]]
## [1] "ITS2-2023-7-29-H7"
## 
## [[106]]
## [1] "ITS2-2023-7-30-H8"
## 
## [[107]]
## [1] "ITS2-2023-7-30-H9"
## 
## [[108]]
## [1] "ITS2-2023-7-5-H1"
## 
## [[109]]
## [1] "ITS2-2023-7-5-H2"
## 
## [[110]]
## [1] "ITS2-2023-7-5-H4"
## 
## [[111]]
## [1] "ITS2-2023-7-6-H6"
## 
## [[112]]
## [1] "ITS2-2023-7-6-H8"
## 
## [[113]]
## [1] "ITS2-2023-7-6-H9"
## 
## [[114]]
## [1] "ITS2-2023-7-8-H3"
## 
## [[115]]
## [1] "ITS2-2023-7-8-H5"
## 
## [[116]]
## [1] "ITS2-2023-7-8-H7"
## 
## [[117]]
## [1] "ITS2-2023-8-4-H2"
## 
## [[118]]
## [1] "ITS2-2023-8-4-H5"
## 
## [[119]]
## [1] "ITS2-2023-8-4-H6"
## 
## [[120]]
## [1] "ITS2-2023-8-4-H7"
## 
## [[121]]
## [1] "ITS2-2023-8-4-H8"
## 
## [[122]]
## [1] "ITS2-2023-8-4-H9"
## 
## [[123]]
## [1] "ITS2-Ba001"
## 
## [[124]]
## [1] "ITS2-Ba002"
## 
## [[125]]
## [1] "ITS2-Ba003"
## 
## [[126]]
## [1] "ITS2-Bb001"
## 
## [[127]]
## [1] "ITS2-Bb002"
## 
## [[128]]
## [1] "ITS2-Bb003"
## 
## [[129]]
## [1] "ITS2-Bb004"
## 
## [[130]]
## [1] "ITS2-Bb005"
## 
## [[131]]
## [1] "ITS2-Bb007"
## 
## [[132]]
## [1] "ITS2-Bb008"
## 
## [[133]]
## [1] "ITS2-Bb009"
## 
## [[134]]
## [1] "ITS2-Bb010"
## 
## [[135]]
## [1] "ITS2-Bb011"
## 
## [[136]]
## [1] "ITS2-Bb012"
## 
## [[137]]
## [1] "ITS2-Bb013"
## 
## [[138]]
## [1] "ITS2-Bb014"
## 
## [[139]]
## [1] "ITS2-Bb015"
## 
## [[140]]
## [1] "ITS2-Bb016"
## 
## [[141]]
## [1] "ITS2-Bb017"
## 
## [[142]]
## [1] "ITS2-Bb018"
## 
## [[143]]
## [1] "ITS2-Bb019"
## 
## [[144]]
## [1] "ITS2-Bb020"
## 
## [[145]]
## [1] "ITS2-Bb021"
## 
## [[146]]
## [1] "ITS2-Bb022"
## 
## [[147]]
## [1] "ITS2-Bb023"
## 
## [[148]]
## [1] "ITS2-Bb024"
## 
## [[149]]
## [1] "ITS2-Bb025"
## 
## [[150]]
## [1] "ITS2-Bf001"
## 
## [[151]]
## [1] "ITS2-Bf002"
## 
## [[152]]
## [1] "ITS2-Bf003"
## 
## [[153]]
## [1] "ITS2-Bf004"
## 
## [[154]]
## [1] "ITS2-Bg001"
## 
## [[155]]
## [1] "ITS2-Bg002"
## 
## [[156]]
## [1] "ITS2-Bg003"
## 
## [[157]]
## [1] "ITS2-Bg004"
## 
## [[158]]
## [1] "ITS2-Bg005"
## 
## [[159]]
## [1] "ITS2-Bg006"
## 
## [[160]]
## [1] "ITS2-Bg007"
## 
## [[161]]
## [1] "ITS2-Bg008"
## 
## [[162]]
## [1] "ITS2-Bg009"
## 
## [[163]]
## [1] "ITS2-Bg010"
## 
## [[164]]
## [1] "ITS2-Bg011"
## 
## [[165]]
## [1] "ITS2-Bg012"
## 
## [[166]]
## [1] "ITS2-Bg013"
## 
## [[167]]
## [1] "ITS2-Bg014"
## 
## [[168]]
## [1] "ITS2-Bg015"
## 
## [[169]]
## [1] "ITS2-Bg016"
## 
## [[170]]
## [1] "ITS2-Bg017"
## 
## [[171]]
## [1] "ITS2-Bg018"
## 
## [[172]]
## [1] "ITS2-Bg019"
## 
## [[173]]
## [1] "ITS2-Bi001"
## 
## [[174]]
## [1] "ITS2-Bi002"
## 
## [[175]]
## [1] "ITS2-Bi003"
## 
## [[176]]
## [1] "ITS2-Bi004"
## 
## [[177]]
## [1] "ITS2-Bi005"
## 
## [[178]]
## [1] "ITS2-Bi006"
## 
## [[179]]
## [1] "ITS2-Bi007"
## 
## [[180]]
## [1] "ITS2-CKC0001"
## 
## [[181]]
## [1] "ITS2-ESE0004"
## 
## [[182]]
## [1] "ITS2-ext-neg-ctrl-20230909"
## 
## [[183]]
## [1] "ITS2-ext-neg-ctrl-20230923"
## 
## [[184]]
## [1] "ITS2-ext-neg-ctrl-20230924"
## 
## [[185]]
## [1] "ITS2-ext-neg-ctrl-20231007"
## 
## [[186]]
## [1] "ITS2-ext-neg-ctrl-20231008"
## 
## [[187]]
## [1] "ITS2-ext-neg-ctrl-20231009"
## 
## [[188]]
## [1] "ITS2-ext-neg-ctrl-2024220A"
## 
## [[189]]
## [1] "ITS2-ext-neg-ctrl-2024220B"
## 
## [[190]]
## [1] "ITS2-ext-neg-ctrl-2024221A"
## 
## [[191]]
## [1] "ITS2-ext-neg-ctrl-2024221B"
## 
## [[192]]
## [1] "ITS2-ext-neg-ctrl-2024222A"
## 
## [[193]]
## [1] "ITS2-ext-neg-ctrl-2024222B"
## 
## [[194]]
## [1] "ITS2-ext-neg-ctrl-2024312A"
## 
## [[195]]
## [1] "ITS2-ext-neg-ctrl-2024312B"
## 
## [[196]]
## [1] "ITS2-ext-neg-ctrl-2024314A"
## 
## [[197]]
## [1] "ITS2-ext-neg-ctrl-2024314B"
## 
## [[198]]
## [1] "ITS2-ext-neg-ctrl-2024319"
## 
## [[199]]
## [1] "ITS2-ext-neg-ctrl-2024320"
## 
## [[200]]
## [1] "ITS2-KLS0007"
## 
## [[201]]
## [1] "ITS2-KLS0027"
## 
## [[202]]
## [1] "ITS2-KLS0044"
## 
## [[203]]
## [1] "ITS2-KLS0045"
## 
## [[204]]
## [1] "ITS2-KLS0052"
## 
## [[205]]
## [1] "ITS2-KLS0054"
## 
## [[206]]
## [1] "ITS2-KLS0055"
## 
## [[207]]
## [1] "ITS2-KLS0071"
## 
## [[208]]
## [1] "ITS2-KLS0095"
## 
## [[209]]
## [1] "ITS2-KLS0096"
## 
## [[210]]
## [1] "ITS2-KLS0105"
## 
## [[211]]
## [1] "ITS2-KLS0106"
## 
## [[212]]
## [1] "ITS2-KLS0119"
## 
## [[213]]
## [1] "ITS2-KLS0134"
## 
## [[214]]
## [1] "ITS2-KLS0135"
## 
## [[215]]
## [1] "ITS2-KLS0136"
## 
## [[216]]
## [1] "ITS2-KLS0137"
## 
## [[217]]
## [1] "ITS2-KLS0138"
## 
## [[218]]
## [1] "ITS2-KLS0139"
## 
## [[219]]
## [1] "ITS2-KLS0150"
## 
## [[220]]
## [1] "ITS2-KLS0153"
## 
## [[221]]
## [1] "ITS2-KLS0155"
## 
## [[222]]
## [1] "ITS2-KLS0156"
## 
## [[223]]
## [1] "ITS2-KLS0159"
## 
## [[224]]
## [1] "ITS2-KLS0163"
## 
## [[225]]
## [1] "ITS2-KLS0165"
## 
## [[226]]
## [1] "ITS2-KLS0167"
## 
## [[227]]
## [1] "ITS2-KLS0168"
## 
## [[228]]
## [1] "ITS2-KLS0169"
## 
## [[229]]
## [1] "ITS2-KLS0170"
## 
## [[230]]
## [1] "ITS2-KLS0200"
## 
## [[231]]
## [1] "ITS2-KLS0201"
## 
## [[232]]
## [1] "ITS2-KLS0205"
## 
## [[233]]
## [1] "ITS2-KLS0209"
## 
## [[234]]
## [1] "ITS2-KLS0221"
## 
## [[235]]
## [1] "ITS2-KLS0224"
## 
## [[236]]
## [1] "ITS2-KLS0225"
## 
## [[237]]
## [1] "ITS2-KLS0227"
## 
## [[238]]
## [1] "ITS2-KLS0241"
## 
## [[239]]
## [1] "ITS2-KLS0244"
## 
## [[240]]
## [1] "ITS2-KLS0246"
## 
## [[241]]
## [1] "ITS2-KLS0248"
## 
## [[242]]
## [1] "ITS2-KLS0253"
## 
## [[243]]
## [1] "ITS2-KLS0254"
## 
## [[244]]
## [1] "ITS2-KLS0256"
## 
## [[245]]
## [1] "ITS2-KLS0259"
## 
## [[246]]
## [1] "ITS2-KLS0263"
## 
## [[247]]
## [1] "ITS2-KLS0266"
## 
## [[248]]
## [1] "ITS2-KLS0272"
## 
## [[249]]
## [1] "ITS2-pcr-its2-neg-ctrl-20231021-20231119"
## 
## [[250]]
## [1] "ITS2-pcr-its2-neg-ctrl-20231022-20231120"
## 
## [[251]]
## [1] "ITS2-pcr-its2-neg-ctrl-20231023"
## 
## [[252]]
## [1] "ITS2-pcr-its2-neg-ctrl-20240411"
## 
## [[253]]
## [1] "ITS2-pcr-its2-neg-ctrl-20240416"
## 
## [[254]]
## [1] "ITS2-pcr-its2-neg-ctrl-20240417"
## 
## [[255]]
## [1] "ITS2-pcr-its2-neg-ctrl-20240418A"
## 
## [[256]]
## [1] "ITS2-pcr-its2-neg-ctrl-20240418B"
## 
## [[257]]
## [1] "ITS2-pcr-its2-neg-ctrl-20240517"
## 
## [[258]]
## [1] "ITS2-pcr-its2-neg-ctrl-20240524"
## 
## [[259]]
## [1] "ITS2-pcr-its2-neg-ctrl-Saskia-20240411"
## 
## [[260]]
## [1] "ITS2-SCA0009"
## 
## [[261]]
## [1] "ITS2-SCA0010"
## 
## [[262]]
## [1] "ITS2-SCA0013"
                  strsplit(sapply(strsplit(rownames(as.data.frame(out)),  "_S"), function(l) l[[1]]),"-")
## [[1]]
## [1] "ITS2" "2020" "6"    "16"   "H1"  
## 
## [[2]]
## [1] "ITS2" "2020" "6"    "16"   "H5"  
## 
## [[3]]
## [1] "ITS2" "2020" "6"    "16"   "H6"  
## 
## [[4]]
## [1] "ITS2" "2020" "6"    "17"   "H2"  
## 
## [[5]]
## [1] "ITS2" "2020" "6"    "17"   "H4"  
## 
## [[6]]
## [1] "ITS2" "2020" "6"    "17"   "H8"  
## 
## [[7]]
## [1] "ITS2" "2020" "6"    "18"   "H3"  
## 
## [[8]]
## [1] "ITS2" "2020" "6"    "18"   "H7"  
## 
## [[9]]
## [1] "ITS2" "2020" "6"    "18"   "H9"  
## 
## [[10]]
## [1] "ITS2" "2020" "6"    "3"    "H1"  
## 
## [[11]]
## [1] "ITS2" "2020" "6"    "3"    "H5"  
## 
## [[12]]
## [1] "ITS2" "2020" "6"    "3"    "H6"  
## 
## [[13]]
## [1] "ITS2" "2020" "6"    "30"   "H1"  
## 
## [[14]]
## [1] "ITS2" "2020" "6"    "30"   "H5"  
## 
## [[15]]
## [1] "ITS2" "2020" "6"    "30"   "H6"  
## 
## [[16]]
## [1] "ITS2" "2020" "6"    "4"    "H2"  
## 
## [[17]]
## [1] "ITS2" "2020" "6"    "4"    "H4"  
## 
## [[18]]
## [1] "ITS2" "2020" "6"    "4"    "H8"  
## 
## [[19]]
## [1] "ITS2" "2020" "6"    "5"    "H3"  
## 
## [[20]]
## [1] "ITS2" "2020" "6"    "5"    "H7"  
## 
## [[21]]
## [1] "ITS2" "2020" "6"    "5"    "H9"  
## 
## [[22]]
## [1] "ITS2" "2020" "7"    "1"    "H2"  
## 
## [[23]]
## [1] "ITS2" "2020" "7"    "1"    "H4"  
## 
## [[24]]
## [1] "ITS2" "2020" "7"    "1"    "H8"  
## 
## [[25]]
## [1] "ITS2" "2020" "7"    "14"   "H1"  
## 
## [[26]]
## [1] "ITS2" "2020" "7"    "14"   "H5"  
## 
## [[27]]
## [1] "ITS2" "2020" "7"    "14"   "H6"  
## 
## [[28]]
## [1] "ITS2" "2020" "7"    "15"   "H2"  
## 
## [[29]]
## [1] "ITS2" "2020" "7"    "15"   "H4"  
## 
## [[30]]
## [1] "ITS2" "2020" "7"    "15"   "H8"  
## 
## [[31]]
## [1] "ITS2" "2020" "7"    "16"   "H3"  
## 
## [[32]]
## [1] "ITS2" "2020" "7"    "16"   "H7"  
## 
## [[33]]
## [1] "ITS2" "2020" "7"    "16"   "H9"  
## 
## [[34]]
## [1] "ITS2" "2020" "7"    "2"    "H3"  
## 
## [[35]]
## [1] "ITS2" "2020" "7"    "2"    "H7"  
## 
## [[36]]
## [1] "ITS2" "2020" "7"    "2"    "H9"  
## 
## [[37]]
## [1] "ITS2" "2021" "6"    "13"   "H1"  
## 
## [[38]]
## [1] "ITS2" "2021" "6"    "13"   "H3"  
## 
## [[39]]
## [1] "ITS2" "2021" "6"    "14"   "H11" 
## 
## [[40]]
## [1] "ITS2" "2021" "6"    "14"   "H6"  
## 
## [[41]]
## [1] "ITS2" "2021" "6"    "14"   "H7"  
## 
## [[42]]
## [1] "ITS2" "2021" "6"    "15"   "H8"  
## 
## [[43]]
## [1] "ITS2" "2021" "6"    "21"   "H10" 
## 
## [[44]]
## [1] "ITS2" "2021" "6"    "21"   "H12" 
## 
## [[45]]
## [1] "ITS2" "2021" "6"    "21"   "H9"  
## 
## [[46]]
## [1] "ITS2" "2021" "6"    "27"   "H21" 
## 
## [[47]]
## [1] "ITS2" "2021" "6"    "27"   "H22" 
## 
## [[48]]
## [1] "ITS2" "2021" "6"    "27"   "H27" 
## 
## [[49]]
## [1] "ITS2" "2021" "6"    "28"   "H25" 
## 
## [[50]]
## [1] "ITS2" "2021" "6"    "28"   "H26" 
## 
## [[51]]
## [1] "ITS2" "2021" "6"    "28"   "H28" 
## 
## [[52]]
## [1] "ITS2" "2021" "6"    "29"   "H17" 
## 
## [[53]]
## [1] "ITS2" "2021" "6"    "29"   "H23" 
## 
## [[54]]
## [1] "ITS2" "2021" "6"    "29"   "H24" 
## 
## [[55]]
## [1] "ITS2" "2021" "6"    "4"    "H21" 
## 
## [[56]]
## [1] "ITS2" "2021" "6"    "4"    "H22" 
## 
## [[57]]
## [1] "ITS2" "2021" "6"    "4"    "H27" 
## 
## [[58]]
## [1] "ITS2" "2021" "6"    "5"    "H18" 
## 
## [[59]]
## [1] "ITS2" "2021" "6"    "5"    "H25" 
## 
## [[60]]
## [1] "ITS2" "2021" "6"    "5"    "H26" 
## 
## [[61]]
## [1] "ITS2" "2021" "6"    "6"    "H17" 
## 
## [[62]]
## [1] "ITS2" "2021" "6"    "6"    "H24" 
## 
## [[63]]
## [1] "ITS2" "2021" "6"    "7"    "H23" 
## 
## [[64]]
## [1] "ITS2" "2021" "7"    "14"   "H10" 
## 
## [[65]]
## [1] "ITS2" "2021" "7"    "14"   "H12" 
## 
## [[66]]
## [1] "ITS2" "2021" "7"    "20"   "H27" 
## 
## [[67]]
## [1] "ITS2" "2021" "7"    "21"   "H25" 
## 
## [[68]]
## [1] "ITS2" "2021" "7"    "21"   "H26" 
## 
## [[69]]
## [1] "ITS2" "2021" "7"    "21"   "H28" 
## 
## [[70]]
## [1] "ITS2" "2021" "7"    "6"    "H11" 
## 
## [[71]]
## [1] "ITS2" "2021" "7"    "6"    "H30" 
## 
## [[72]]
## [1] "ITS2" "2021" "7"    "6"    "H6"  
## 
## [[73]]
## [1] "ITS2" "2021" "7"    "7"    "H4"  
## 
## [[74]]
## [1] "ITS2" "2021" "7"    "7"    "H8"  
## 
## [[75]]
## [1] "ITS2" "2021" "7"    "8"    "H3"  
## 
## [[76]]
## [1] "ITS2" "2023" "6"    "12"   "H3"  
## 
## [[77]]
## [1] "ITS2" "2023" "6"    "12"   "H5"  
## 
## [[78]]
## [1] "ITS2" "2023" "6"    "12"   "H7"  
## 
## [[79]]
## [1] "ITS2" "2023" "6"    "13"   "H6"  
## 
## [[80]]
## [1] "ITS2" "2023" "6"    "13"   "H8"  
## 
## [[81]]
## [1] "ITS2" "2023" "6"    "13"   "H9"  
## 
## [[82]]
## [1] "ITS2" "2023" "6"    "14"   "H3"  
## 
## [[83]]
## [1] "ITS2" "2023" "6"    "14"   "H7"  
## 
## [[84]]
## [1] "ITS2" "2023" "6"    "14"   "H9"  
## 
## [[85]]
## [1] "ITS2" "2023" "6"    "16"   "H5"  
## 
## [[86]]
## [1] "ITS2" "2023" "6"    "24"   "H6"  
## 
## [[87]]
## [1] "ITS2" "2023" "6"    "24"   "H8"  
## 
## [[88]]
## [1] "ITS2" "2023" "6"    "25"   "H2"  
## 
## [[89]]
## [1] "ITS2" "2023" "6"    "25"   "H4"  
## 
## [[90]]
## [1] "ITS2" "2023" "6"    "26"   "H1"  
## 
## [[91]]
## [1] "ITS2" "2023" "6"    "26"   "H7"  
## 
## [[92]]
## [1] "ITS2" "2023" "6"    "27"   "H3"  
## 
## [[93]]
## [1] "ITS2" "2023" "6"    "27"   "H5"  
## 
## [[94]]
## [1] "ITS2" "2023" "6"    "8"    "H1"  
## 
## [[95]]
## [1] "ITS2" "2023" "6"    "8"    "H2"  
## 
## [[96]]
## [1] "ITS2" "2023" "6"    "8"    "H4"  
## 
## [[97]]
## [1] "ITS2" "2023" "6"    "9"    "H2"  
## 
## [[98]]
## [1] "ITS2" "2023" "6"    "9"    "H4"  
## 
## [[99]]
## [1] "ITS2" "2023" "7"    "15"   "H6"  
## 
## [[100]]
## [1] "ITS2" "2023" "7"    "16"   "H4"  
## 
## [[101]]
## [1] "ITS2" "2023" "7"    "17"   "H1"  
## 
## [[102]]
## [1] "ITS2" "2023" "7"    "18"   "H3"  
## 
## [[103]]
## [1] "ITS2" "2023" "7"    "18"   "H7"  
## 
## [[104]]
## [1] "ITS2" "2023" "7"    "29"   "H5"  
## 
## [[105]]
## [1] "ITS2" "2023" "7"    "29"   "H7"  
## 
## [[106]]
## [1] "ITS2" "2023" "7"    "30"   "H8"  
## 
## [[107]]
## [1] "ITS2" "2023" "7"    "30"   "H9"  
## 
## [[108]]
## [1] "ITS2" "2023" "7"    "5"    "H1"  
## 
## [[109]]
## [1] "ITS2" "2023" "7"    "5"    "H2"  
## 
## [[110]]
## [1] "ITS2" "2023" "7"    "5"    "H4"  
## 
## [[111]]
## [1] "ITS2" "2023" "7"    "6"    "H6"  
## 
## [[112]]
## [1] "ITS2" "2023" "7"    "6"    "H8"  
## 
## [[113]]
## [1] "ITS2" "2023" "7"    "6"    "H9"  
## 
## [[114]]
## [1] "ITS2" "2023" "7"    "8"    "H3"  
## 
## [[115]]
## [1] "ITS2" "2023" "7"    "8"    "H5"  
## 
## [[116]]
## [1] "ITS2" "2023" "7"    "8"    "H7"  
## 
## [[117]]
## [1] "ITS2" "2023" "8"    "4"    "H2"  
## 
## [[118]]
## [1] "ITS2" "2023" "8"    "4"    "H5"  
## 
## [[119]]
## [1] "ITS2" "2023" "8"    "4"    "H6"  
## 
## [[120]]
## [1] "ITS2" "2023" "8"    "4"    "H7"  
## 
## [[121]]
## [1] "ITS2" "2023" "8"    "4"    "H8"  
## 
## [[122]]
## [1] "ITS2" "2023" "8"    "4"    "H9"  
## 
## [[123]]
## [1] "ITS2"  "Ba001"
## 
## [[124]]
## [1] "ITS2"  "Ba002"
## 
## [[125]]
## [1] "ITS2"  "Ba003"
## 
## [[126]]
## [1] "ITS2"  "Bb001"
## 
## [[127]]
## [1] "ITS2"  "Bb002"
## 
## [[128]]
## [1] "ITS2"  "Bb003"
## 
## [[129]]
## [1] "ITS2"  "Bb004"
## 
## [[130]]
## [1] "ITS2"  "Bb005"
## 
## [[131]]
## [1] "ITS2"  "Bb007"
## 
## [[132]]
## [1] "ITS2"  "Bb008"
## 
## [[133]]
## [1] "ITS2"  "Bb009"
## 
## [[134]]
## [1] "ITS2"  "Bb010"
## 
## [[135]]
## [1] "ITS2"  "Bb011"
## 
## [[136]]
## [1] "ITS2"  "Bb012"
## 
## [[137]]
## [1] "ITS2"  "Bb013"
## 
## [[138]]
## [1] "ITS2"  "Bb014"
## 
## [[139]]
## [1] "ITS2"  "Bb015"
## 
## [[140]]
## [1] "ITS2"  "Bb016"
## 
## [[141]]
## [1] "ITS2"  "Bb017"
## 
## [[142]]
## [1] "ITS2"  "Bb018"
## 
## [[143]]
## [1] "ITS2"  "Bb019"
## 
## [[144]]
## [1] "ITS2"  "Bb020"
## 
## [[145]]
## [1] "ITS2"  "Bb021"
## 
## [[146]]
## [1] "ITS2"  "Bb022"
## 
## [[147]]
## [1] "ITS2"  "Bb023"
## 
## [[148]]
## [1] "ITS2"  "Bb024"
## 
## [[149]]
## [1] "ITS2"  "Bb025"
## 
## [[150]]
## [1] "ITS2"  "Bf001"
## 
## [[151]]
## [1] "ITS2"  "Bf002"
## 
## [[152]]
## [1] "ITS2"  "Bf003"
## 
## [[153]]
## [1] "ITS2"  "Bf004"
## 
## [[154]]
## [1] "ITS2"  "Bg001"
## 
## [[155]]
## [1] "ITS2"  "Bg002"
## 
## [[156]]
## [1] "ITS2"  "Bg003"
## 
## [[157]]
## [1] "ITS2"  "Bg004"
## 
## [[158]]
## [1] "ITS2"  "Bg005"
## 
## [[159]]
## [1] "ITS2"  "Bg006"
## 
## [[160]]
## [1] "ITS2"  "Bg007"
## 
## [[161]]
## [1] "ITS2"  "Bg008"
## 
## [[162]]
## [1] "ITS2"  "Bg009"
## 
## [[163]]
## [1] "ITS2"  "Bg010"
## 
## [[164]]
## [1] "ITS2"  "Bg011"
## 
## [[165]]
## [1] "ITS2"  "Bg012"
## 
## [[166]]
## [1] "ITS2"  "Bg013"
## 
## [[167]]
## [1] "ITS2"  "Bg014"
## 
## [[168]]
## [1] "ITS2"  "Bg015"
## 
## [[169]]
## [1] "ITS2"  "Bg016"
## 
## [[170]]
## [1] "ITS2"  "Bg017"
## 
## [[171]]
## [1] "ITS2"  "Bg018"
## 
## [[172]]
## [1] "ITS2"  "Bg019"
## 
## [[173]]
## [1] "ITS2"  "Bi001"
## 
## [[174]]
## [1] "ITS2"  "Bi002"
## 
## [[175]]
## [1] "ITS2"  "Bi003"
## 
## [[176]]
## [1] "ITS2"  "Bi004"
## 
## [[177]]
## [1] "ITS2"  "Bi005"
## 
## [[178]]
## [1] "ITS2"  "Bi006"
## 
## [[179]]
## [1] "ITS2"  "Bi007"
## 
## [[180]]
## [1] "ITS2"    "CKC0001"
## 
## [[181]]
## [1] "ITS2"    "ESE0004"
## 
## [[182]]
## [1] "ITS2"     "ext"      "neg"      "ctrl"     "20230909"
## 
## [[183]]
## [1] "ITS2"     "ext"      "neg"      "ctrl"     "20230923"
## 
## [[184]]
## [1] "ITS2"     "ext"      "neg"      "ctrl"     "20230924"
## 
## [[185]]
## [1] "ITS2"     "ext"      "neg"      "ctrl"     "20231007"
## 
## [[186]]
## [1] "ITS2"     "ext"      "neg"      "ctrl"     "20231008"
## 
## [[187]]
## [1] "ITS2"     "ext"      "neg"      "ctrl"     "20231009"
## 
## [[188]]
## [1] "ITS2"     "ext"      "neg"      "ctrl"     "2024220A"
## 
## [[189]]
## [1] "ITS2"     "ext"      "neg"      "ctrl"     "2024220B"
## 
## [[190]]
## [1] "ITS2"     "ext"      "neg"      "ctrl"     "2024221A"
## 
## [[191]]
## [1] "ITS2"     "ext"      "neg"      "ctrl"     "2024221B"
## 
## [[192]]
## [1] "ITS2"     "ext"      "neg"      "ctrl"     "2024222A"
## 
## [[193]]
## [1] "ITS2"     "ext"      "neg"      "ctrl"     "2024222B"
## 
## [[194]]
## [1] "ITS2"     "ext"      "neg"      "ctrl"     "2024312A"
## 
## [[195]]
## [1] "ITS2"     "ext"      "neg"      "ctrl"     "2024312B"
## 
## [[196]]
## [1] "ITS2"     "ext"      "neg"      "ctrl"     "2024314A"
## 
## [[197]]
## [1] "ITS2"     "ext"      "neg"      "ctrl"     "2024314B"
## 
## [[198]]
## [1] "ITS2"    "ext"     "neg"     "ctrl"    "2024319"
## 
## [[199]]
## [1] "ITS2"    "ext"     "neg"     "ctrl"    "2024320"
## 
## [[200]]
## [1] "ITS2"    "KLS0007"
## 
## [[201]]
## [1] "ITS2"    "KLS0027"
## 
## [[202]]
## [1] "ITS2"    "KLS0044"
## 
## [[203]]
## [1] "ITS2"    "KLS0045"
## 
## [[204]]
## [1] "ITS2"    "KLS0052"
## 
## [[205]]
## [1] "ITS2"    "KLS0054"
## 
## [[206]]
## [1] "ITS2"    "KLS0055"
## 
## [[207]]
## [1] "ITS2"    "KLS0071"
## 
## [[208]]
## [1] "ITS2"    "KLS0095"
## 
## [[209]]
## [1] "ITS2"    "KLS0096"
## 
## [[210]]
## [1] "ITS2"    "KLS0105"
## 
## [[211]]
## [1] "ITS2"    "KLS0106"
## 
## [[212]]
## [1] "ITS2"    "KLS0119"
## 
## [[213]]
## [1] "ITS2"    "KLS0134"
## 
## [[214]]
## [1] "ITS2"    "KLS0135"
## 
## [[215]]
## [1] "ITS2"    "KLS0136"
## 
## [[216]]
## [1] "ITS2"    "KLS0137"
## 
## [[217]]
## [1] "ITS2"    "KLS0138"
## 
## [[218]]
## [1] "ITS2"    "KLS0139"
## 
## [[219]]
## [1] "ITS2"    "KLS0150"
## 
## [[220]]
## [1] "ITS2"    "KLS0153"
## 
## [[221]]
## [1] "ITS2"    "KLS0155"
## 
## [[222]]
## [1] "ITS2"    "KLS0156"
## 
## [[223]]
## [1] "ITS2"    "KLS0159"
## 
## [[224]]
## [1] "ITS2"    "KLS0163"
## 
## [[225]]
## [1] "ITS2"    "KLS0165"
## 
## [[226]]
## [1] "ITS2"    "KLS0167"
## 
## [[227]]
## [1] "ITS2"    "KLS0168"
## 
## [[228]]
## [1] "ITS2"    "KLS0169"
## 
## [[229]]
## [1] "ITS2"    "KLS0170"
## 
## [[230]]
## [1] "ITS2"    "KLS0200"
## 
## [[231]]
## [1] "ITS2"    "KLS0201"
## 
## [[232]]
## [1] "ITS2"    "KLS0205"
## 
## [[233]]
## [1] "ITS2"    "KLS0209"
## 
## [[234]]
## [1] "ITS2"    "KLS0221"
## 
## [[235]]
## [1] "ITS2"    "KLS0224"
## 
## [[236]]
## [1] "ITS2"    "KLS0225"
## 
## [[237]]
## [1] "ITS2"    "KLS0227"
## 
## [[238]]
## [1] "ITS2"    "KLS0241"
## 
## [[239]]
## [1] "ITS2"    "KLS0244"
## 
## [[240]]
## [1] "ITS2"    "KLS0246"
## 
## [[241]]
## [1] "ITS2"    "KLS0248"
## 
## [[242]]
## [1] "ITS2"    "KLS0253"
## 
## [[243]]
## [1] "ITS2"    "KLS0254"
## 
## [[244]]
## [1] "ITS2"    "KLS0256"
## 
## [[245]]
## [1] "ITS2"    "KLS0259"
## 
## [[246]]
## [1] "ITS2"    "KLS0263"
## 
## [[247]]
## [1] "ITS2"    "KLS0266"
## 
## [[248]]
## [1] "ITS2"    "KLS0272"
## 
## [[249]]
## [1] "ITS2"     "pcr"      "its2"     "neg"      "ctrl"     "20231021" "20231119"
## 
## [[250]]
## [1] "ITS2"     "pcr"      "its2"     "neg"      "ctrl"     "20231022" "20231120"
## 
## [[251]]
## [1] "ITS2"     "pcr"      "its2"     "neg"      "ctrl"     "20231023"
## 
## [[252]]
## [1] "ITS2"     "pcr"      "its2"     "neg"      "ctrl"     "20240411"
## 
## [[253]]
## [1] "ITS2"     "pcr"      "its2"     "neg"      "ctrl"     "20240416"
## 
## [[254]]
## [1] "ITS2"     "pcr"      "its2"     "neg"      "ctrl"     "20240417"
## 
## [[255]]
## [1] "ITS2"      "pcr"       "its2"      "neg"       "ctrl"      "20240418A"
## 
## [[256]]
## [1] "ITS2"      "pcr"       "its2"      "neg"       "ctrl"      "20240418B"
## 
## [[257]]
## [1] "ITS2"     "pcr"      "its2"     "neg"      "ctrl"     "20240517"
## 
## [[258]]
## [1] "ITS2"     "pcr"      "its2"     "neg"      "ctrl"     "20240524"
## 
## [[259]]
## [1] "ITS2"     "pcr"      "its2"     "neg"      "ctrl"     "Saskia"   "20240411"
## 
## [[260]]
## [1] "ITS2"    "SCA0009"
## 
## [[261]]
## [1] "ITS2"    "SCA0010"
## 
## [[262]]
## [1] "ITS2"    "SCA0013"
                  strsplit(sapply(strsplit(rownames(as.data.frame(out)),  "_S"), function(l) l[[1]]),"-")[[1]][-1]
## [1] "2020" "6"    "16"   "H1"
            temp<-strsplit(sapply(strsplit(rownames(as.data.frame(out)),  "_S"), function(l) l[[1]]),"-")

sample.names<-character(length(rownames(as.data.frame(out)))) #set up container object
for(i in 1:length(rownames(as.data.frame(out)))){ #fill container with sample names
  sample.names[i]<-paste(temp[[i]][-1],collapse="_")
}
head(sample.names); tail(sample.names); length(sample.names); length(rownames(out)) #sample.names, length of sample.names, length of samples output from filterAndTrim
## [1] "2020_6_16_H1" "2020_6_16_H5" "2020_6_16_H6" "2020_6_17_H2" "2020_6_17_H4"
## [6] "2020_6_17_H8"
## [1] "pcr_its2_neg_ctrl_20240517"        "pcr_its2_neg_ctrl_20240524"       
## [3] "pcr_its2_neg_ctrl_Saskia_20240411" "SCA0009"                          
## [5] "SCA0010"                           "SCA0013"
## [1] 262
## [1] 262
rownames(out)<-sample.names

Not every sample made it through the filterAndTrim step

length(file.path(path.cut, "filtered", basename(cutFs))) #length of "filtFs," created in chunk above (262)
## [1] 262
length(list.files(file.path(path.cut, "filtered"), pattern = "L001_R1_001.fastq", full.names = TRUE)) #length of files actually written to the filtFs directories (254)
## [1] 254

Updating path names (after samples drop out)

# update directory, since not all samples made it thru the filter
filtFs <- file.path(path.cut, "filtered", basename(list.files(file.path(path.cut, "filtered"), pattern = "L001_R1_001.fastq", full.names = TRUE)))
filtRs <- file.path(path.cut, "filtered", basename(list.files(file.path(path.cut, "filtered"), pattern = "L001_R2_001.fastq", full.names = TRUE)))

Learn error and inspect quality of cutadapted & filtered reads

##Learn the error rates Learns the error rates from an input list, or vector, of file names or a list of derep-class objects. Error rate estimation is performed by errorEstimationFunction. The output of this function serves as input to the dada function call as the err parameter

This uses the reads from the filter and trimmed files located in the “filtered” folder /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered

#You can safely ignore error messages “Not all sequences were the same length.”
errF <- learnErrors(filtFs, multithread = TRUE)
## 104372214 total bases in 371645 reads from 35 samples will be used for learning the error rates.
errR <- learnErrors(filtRs, multithread = TRUE)
## 104475633 total bases in 371645 reads from 35 samples will be used for learning the error rates.
#explanation of parameters in the learnErrors() function:
#learnErrors(
            #fls,             <-- fastq files
            #nbases = 1e+08,   <-- minimum number of total bases to learn error rate
            #nreads = NULL,   <-- deprecated, don't use
            #errorEstimationFunction = loessErrfun,
            #multithread = FALSE, <-- if enabled, sets the number of threads
            #randomize = FALSE,  <-- If FALSE, samples are read in the provided order until enough reads are obtained. If TRUE, samples are picked at random from those provided
            #MAX_CONSIST = 10,  <--The maximum number of times to step through the self-consistency loop.
            #OMEGA_C = 0,  <--The threshold at which unique sequences inferred to contain errors are corrected in the final output, and used to estimate the error rates
            #qualityType = "Auto", <--The quality encoding of the fastq file(s). "Auto" (the default) means to attempt to auto-detect the encoding.
            #verbose = FALSE)

Plot errors

We expect a roughly linear decrease in Log transformed error frequency as the consensus quality score increases from 0 to 40

plotErrors(errF, nominalQ = TRUE) #forward
## Warning in scale_y_log10(): log-10 transformation introduced infinite values.

plotErrors(errR, nominalQ = TRUE) #reverse
## Warning in scale_y_log10(): log-10 transformation introduced infinite values.

Inspect read quality profiles

The quality profile plot is a gray-scale heatmap of the frequency of each quality score at each base position. The median quality score at each position is shown by the green line, and the quartiles of the quality score distribution by the orange lines. The read line shows the scaled proportion of reads that extend to at least that position.

plotQualityProfile(filtFs[n]) #inspect nth sample's forward reads

plotQualityProfile(filtRs[n]) #reverse always worse

Dereplication & denoising of identical sequences

Dereplication combines all identical sequencing reads into into “unique sequences” with a corresponding “abundance” (the number of reads with that same sequence). Dereplication substantially reduces computation time by eliminating redundant comparisons.

DADA2 retains a summary of the quality information associated with each unique sequence. The consensus quality profile of a unique sequence is the average of the positional qualities from the dereplicated reads. These quality profiles inform the error model of the subsequent denoising step, significantly increasing DADA2’s accuracy. But we did the learnErrors step before dereplication? dada is the denoising step and uses the error model created before

using the reads from the filter and trimmed files located in the “filtered” folder /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered

##Dereplicate reads

derepFs <- derepFastq(filtFs, verbose = TRUE)
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-16-H1_S31_L001_R1_001.fastq
## Encountered 2 unique sequences from 2 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-16-H5_S32_L001_R1_001.fastq
## Encountered 3 unique sequences from 3 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-16-H6_S33_L001_R1_001.fastq
## Encountered 1 unique sequences from 1 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-17-H2_S34_L001_R1_001.fastq
## Encountered 7 unique sequences from 7 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-17-H4_S35_L001_R1_001.fastq
## Encountered 8 unique sequences from 8 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-17-H8_S36_L001_R1_001.fastq
## Encountered 5 unique sequences from 5 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-18-H3_S37_L001_R1_001.fastq
## Encountered 6411 unique sequences from 28544 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-18-H7_S38_L001_R1_001.fastq
## Encountered 3101 unique sequences from 14114 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-18-H9_S39_L001_R1_001.fastq
## Encountered 2768 unique sequences from 9775 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-3-H1_S40_L001_R1_001.fastq
## Encountered 4015 unique sequences from 17562 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-3-H5_S41_L001_R1_001.fastq
## Encountered 3747 unique sequences from 17183 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-3-H6_S42_L001_R1_001.fastq
## Encountered 2460 unique sequences from 9113 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-30-H1_S43_L001_R1_001.fastq
## Encountered 3335 unique sequences from 11400 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-30-H6_S45_L001_R1_001.fastq
## Encountered 1 unique sequences from 1 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-4-H2_S46_L001_R1_001.fastq
## Encountered 1627 unique sequences from 3807 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-4-H4_S47_L001_R1_001.fastq
## Encountered 2493 unique sequences from 7207 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-4-H8_S48_L001_R1_001.fastq
## Encountered 4403 unique sequences from 20412 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-5-H3_S49_L001_R1_001.fastq
## Encountered 3161 unique sequences from 13330 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-5-H7_S50_L001_R1_001.fastq
## Encountered 3277 unique sequences from 13763 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-5-H9_S51_L001_R1_001.fastq
## Encountered 2 unique sequences from 2 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-7-1-H2_S52_L001_R1_001.fastq
## Encountered 1 unique sequences from 1 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-7-1-H4_S53_L001_R1_001.fastq
## Encountered 3 unique sequences from 3 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-7-1-H8_S54_L001_R1_001.fastq
## Encountered 8478 unique sequences from 59663 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-7-14-H1_S55_L001_R1_001.fastq
## Encountered 24 unique sequences from 54 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-7-14-H5_S56_L001_R1_001.fastq
## Encountered 6274 unique sequences from 25171 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-7-14-H6_S57_L001_R1_001.fastq
## Encountered 5803 unique sequences from 25820 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-7-15-H4_S59_L001_R1_001.fastq
## Encountered 4 unique sequences from 4 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-7-15-H8_S60_L001_R1_001.fastq
## Encountered 3 unique sequences from 3 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-7-16-H3_S61_L001_R1_001.fastq
## Encountered 4 unique sequences from 4 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-7-16-H9_S63_L001_R1_001.fastq
## Encountered 2 unique sequences from 2 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-7-2-H3_S64_L001_R1_001.fastq
## Encountered 5547 unique sequences from 19284 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-7-2-H7_S65_L001_R1_001.fastq
## Encountered 4022 unique sequences from 14455 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-7-2-H9_S66_L001_R1_001.fastq
## Encountered 2140 unique sequences from 7696 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-13-H1_S67_L001_R1_001.fastq
## Encountered 5141 unique sequences from 33662 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-13-H3_S68_L001_R1_001.fastq
## Encountered 4338 unique sequences from 19584 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-14-H11_S69_L001_R1_001.fastq
## Encountered 5338 unique sequences from 30473 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-14-H6_S70_L001_R1_001.fastq
## Encountered 4070 unique sequences from 21451 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-14-H7_S71_L001_R1_001.fastq
## Encountered 4454 unique sequences from 27667 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-15-H8_S72_L001_R1_001.fastq
## Encountered 5768 unique sequences from 29183 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-21-H10_S73_L001_R1_001.fastq
## Encountered 4572 unique sequences from 22468 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-21-H12_S74_L001_R1_001.fastq
## Encountered 2949 unique sequences from 15386 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-21-H9_S75_L001_R1_001.fastq
## Encountered 4394 unique sequences from 22706 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-27-H21_S76_L001_R1_001.fastq
## Encountered 3341 unique sequences from 13598 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-27-H22_S77_L001_R1_001.fastq
## Encountered 2965 unique sequences from 16586 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-27-H27_S78_L001_R1_001.fastq
## Encountered 2829 unique sequences from 11031 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-28-H25_S79_L001_R1_001.fastq
## Encountered 6110 unique sequences from 37109 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-28-H26_S80_L001_R1_001.fastq
## Encountered 4087 unique sequences from 18011 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-28-H28_S81_L001_R1_001.fastq
## Encountered 7181 unique sequences from 24520 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-29-H17_S82_L001_R1_001.fastq
## Encountered 4809 unique sequences from 20380 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-29-H23_S83_L001_R1_001.fastq
## Encountered 3259 unique sequences from 15119 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-29-H24_S84_L001_R1_001.fastq
## Encountered 4177 unique sequences from 23804 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-4-H21_S85_L001_R1_001.fastq
## Encountered 2410 unique sequences from 7846 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-4-H22_S86_L001_R1_001.fastq
## Encountered 5726 unique sequences from 32343 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-4-H27_S87_L001_R1_001.fastq
## Encountered 1388 unique sequences from 4382 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-5-H18_S88_L001_R1_001.fastq
## Encountered 2268 unique sequences from 8700 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-5-H25_S89_L001_R1_001.fastq
## Encountered 1757 unique sequences from 6167 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-5-H26_S90_L001_R1_001.fastq
## Encountered 6992 unique sequences from 30751 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-6-H17_S91_L001_R1_001.fastq
## Encountered 2556 unique sequences from 9885 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-6-H24_S92_L001_R1_001.fastq
## Encountered 5879 unique sequences from 27479 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-7-H23_S93_L001_R1_001.fastq
## Encountered 2630 unique sequences from 10700 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-7-14-H10_S94_L001_R1_001.fastq
## Encountered 2867 unique sequences from 17609 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-7-20-H27_S96_L001_R1_001.fastq
## Encountered 3138 unique sequences from 12038 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-7-21-H25_S97_L001_R1_001.fastq
## Encountered 3041 unique sequences from 16172 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-7-21-H26_S98_L001_R1_001.fastq
## Encountered 6 unique sequences from 6 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-7-21-H28_S99_L001_R1_001.fastq
## Encountered 2 unique sequences from 2 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-7-6-H11_S100_L001_R1_001.fastq
## Encountered 6533 unique sequences from 23260 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-7-6-H30_S101_L001_R1_001.fastq
## Encountered 1 unique sequences from 1 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-7-6-H6_S102_L001_R1_001.fastq
## Encountered 3537 unique sequences from 12438 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-7-7-H8_S104_L001_R1_001.fastq
## Encountered 3627 unique sequences from 23534 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-7-8-H3_S105_L001_R1_001.fastq
## Encountered 4064 unique sequences from 23041 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-12-H3_S106_L001_R1_001.fastq
## Encountered 2883 unique sequences from 12263 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-12-H5_S107_L001_R1_001.fastq
## Encountered 4865 unique sequences from 24829 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-12-H7_S108_L001_R1_001.fastq
## Encountered 1895 unique sequences from 6086 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-13-H6_S109_L001_R1_001.fastq
## Encountered 2828 unique sequences from 13625 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-13-H8_S110_L001_R1_001.fastq
## Encountered 3772 unique sequences from 15490 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-13-H9_S111_L001_R1_001.fastq
## Encountered 3407 unique sequences from 19503 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-14-H3_S112_L001_R1_001.fastq
## Encountered 3942 unique sequences from 20699 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-14-H7_S113_L001_R1_001.fastq
## Encountered 6335 unique sequences from 33188 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-14-H9_S114_L001_R1_001.fastq
## Encountered 6508 unique sequences from 37485 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-16-H5_S115_L001_R1_001.fastq
## Encountered 3705 unique sequences from 15022 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-24-H6_S116_L001_R1_001.fastq
## Encountered 7751 unique sequences from 34675 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-24-H8_S117_L001_R1_001.fastq
## Encountered 4903 unique sequences from 17439 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-25-H2_S118_L001_R1_001.fastq
## Encountered 7986 unique sequences from 31265 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-25-H4_S119_L001_R1_001.fastq
## Encountered 6969 unique sequences from 31537 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-26-H1_S120_L001_R1_001.fastq
## Encountered 3225 unique sequences from 8136 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-26-H7_S121_L001_R1_001.fastq
## Encountered 5999 unique sequences from 24821 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-27-H3_S122_L001_R1_001.fastq
## Encountered 2902 unique sequences from 10606 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-27-H5_S123_L001_R1_001.fastq
## Encountered 4567 unique sequences from 16479 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-8-H1_S124_L001_R1_001.fastq
## Encountered 5088 unique sequences from 21254 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-8-H2_S125_L001_R1_001.fastq
## Encountered 3050 unique sequences from 16527 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-8-H4_S126_L001_R1_001.fastq
## Encountered 5349 unique sequences from 38333 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-9-H2_S127_L001_R1_001.fastq
## Encountered 3228 unique sequences from 14590 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-9-H4_S128_L001_R1_001.fastq
## Encountered 4381 unique sequences from 22545 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-15-H6_S129_L001_R1_001.fastq
## Encountered 5373 unique sequences from 23983 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-16-H4_S130_L001_R1_001.fastq
## Encountered 5533 unique sequences from 29295 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-17-H1_S131_L001_R1_001.fastq
## Encountered 3654 unique sequences from 14894 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-18-H3_S132_L001_R1_001.fastq
## Encountered 5279 unique sequences from 21650 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-18-H7_S133_L001_R1_001.fastq
## Encountered 2367 unique sequences from 12527 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-29-H5_S134_L001_R1_001.fastq
## Encountered 5393 unique sequences from 25406 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-29-H7_S135_L001_R1_001.fastq
## Encountered 7171 unique sequences from 40098 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-30-H8_S136_L001_R1_001.fastq
## Encountered 5008 unique sequences from 27389 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-30-H9_S137_L001_R1_001.fastq
## Encountered 7051 unique sequences from 42773 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-5-H1_S138_L001_R1_001.fastq
## Encountered 3099 unique sequences from 18663 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-5-H2_S139_L001_R1_001.fastq
## Encountered 3874 unique sequences from 24683 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-5-H4_S140_L001_R1_001.fastq
## Encountered 2963 unique sequences from 16886 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-6-H6_S141_L001_R1_001.fastq
## Encountered 3889 unique sequences from 23320 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-6-H8_S142_L001_R1_001.fastq
## Encountered 4410 unique sequences from 25858 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-6-H9_S143_L001_R1_001.fastq
## Encountered 6979 unique sequences from 37973 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-8-H3_S144_L001_R1_001.fastq
## Encountered 2995 unique sequences from 14762 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-8-H5_S145_L001_R1_001.fastq
## Encountered 2382 unique sequences from 16132 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-8-H7_S146_L001_R1_001.fastq
## Encountered 4194 unique sequences from 24378 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-8-4-H2_S147_L001_R1_001.fastq
## Encountered 3737 unique sequences from 23680 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-8-4-H5_S148_L001_R1_001.fastq
## Encountered 7584 unique sequences from 34917 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-8-4-H6_S149_L001_R1_001.fastq
## Encountered 3819 unique sequences from 15791 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-8-4-H7_S150_L001_R1_001.fastq
## Encountered 5292 unique sequences from 19770 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-8-4-H8_S151_L001_R1_001.fastq
## Encountered 4401 unique sequences from 17643 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-8-4-H9_S152_L001_R1_001.fastq
## Encountered 4314 unique sequences from 14039 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Ba001_S153_L001_R1_001.fastq
## Encountered 3129 unique sequences from 10777 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Ba002_S154_L001_R1_001.fastq
## Encountered 1886 unique sequences from 5537 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Ba003_S155_L001_R1_001.fastq
## Encountered 3998 unique sequences from 9074 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb001_S156_L001_R1_001.fastq
## Encountered 1888 unique sequences from 6275 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb002_S157_L001_R1_001.fastq
## Encountered 2159 unique sequences from 7357 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb003_S158_L001_R1_001.fastq
## Encountered 3197 unique sequences from 11309 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb004_S159_L001_R1_001.fastq
## Encountered 3109 unique sequences from 10220 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb005_S160_L001_R1_001.fastq
## Encountered 1556 unique sequences from 5421 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb007_S161_L001_R1_001.fastq
## Encountered 309 unique sequences from 1227 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb008_S162_L001_R1_001.fastq
## Encountered 884 unique sequences from 3419 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb009_S163_L001_R1_001.fastq
## Encountered 585 unique sequences from 2193 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb010_S164_L001_R1_001.fastq
## Encountered 3182 unique sequences from 8989 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb011_S165_L001_R1_001.fastq
## Encountered 1819 unique sequences from 5075 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb012_S166_L001_R1_001.fastq
## Encountered 3718 unique sequences from 15928 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb013_S167_L001_R1_001.fastq
## Encountered 2077 unique sequences from 6123 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb014_S168_L001_R1_001.fastq
## Encountered 1087 unique sequences from 3127 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb015_S169_L001_R1_001.fastq
## Encountered 1103 unique sequences from 3045 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb016_S170_L001_R1_001.fastq
## Encountered 124 unique sequences from 318 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb017_S171_L001_R1_001.fastq
## Encountered 742 unique sequences from 2279 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb018_S172_L001_R1_001.fastq
## Encountered 2031 unique sequences from 5380 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb019_S173_L001_R1_001.fastq
## Encountered 2438 unique sequences from 8859 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb020_S174_L001_R1_001.fastq
## Encountered 1302 unique sequences from 6218 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb021_S175_L001_R1_001.fastq
## Encountered 4100 unique sequences from 13981 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb022_S176_L001_R1_001.fastq
## Encountered 5105 unique sequences from 24593 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb023_S177_L001_R1_001.fastq
## Encountered 4617 unique sequences from 24923 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb024_S178_L001_R1_001.fastq
## Encountered 5541 unique sequences from 36400 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb025_S179_L001_R1_001.fastq
## Encountered 3804 unique sequences from 16550 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bf001_S180_L001_R1_001.fastq
## Encountered 3964 unique sequences from 22204 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bf002_S181_L001_R1_001.fastq
## Encountered 3447 unique sequences from 18314 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bf003_S182_L001_R1_001.fastq
## Encountered 4327 unique sequences from 28486 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bf004_S183_L001_R1_001.fastq
## Encountered 4943 unique sequences from 20792 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg001_S184_L001_R1_001.fastq
## Encountered 5227 unique sequences from 19460 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg002_S185_L001_R1_001.fastq
## Encountered 4239 unique sequences from 14410 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg003_S186_L001_R1_001.fastq
## Encountered 7289 unique sequences from 31643 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg004_S187_L001_R1_001.fastq
## Encountered 6501 unique sequences from 21133 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg005_S188_L001_R1_001.fastq
## Encountered 4026 unique sequences from 18459 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg006_S189_L001_R1_001.fastq
## Encountered 7585 unique sequences from 30218 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg007_S190_L001_R1_001.fastq
## Encountered 3071 unique sequences from 14612 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg008_S191_L001_R1_001.fastq
## Encountered 3225 unique sequences from 12218 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg009_S192_L001_R1_001.fastq
## Encountered 5073 unique sequences from 21107 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg010_S193_L001_R1_001.fastq
## Encountered 7453 unique sequences from 35028 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg011_S194_L001_R1_001.fastq
## Encountered 5894 unique sequences from 25569 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg012_S195_L001_R1_001.fastq
## Encountered 6000 unique sequences from 32557 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg013_S196_L001_R1_001.fastq
## Encountered 2861 unique sequences from 11893 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg014_S197_L001_R1_001.fastq
## Encountered 3897 unique sequences from 23693 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg015_S198_L001_R1_001.fastq
## Encountered 3853 unique sequences from 17641 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg016_S199_L001_R1_001.fastq
## Encountered 2884 unique sequences from 15525 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg017_S200_L001_R1_001.fastq
## Encountered 3301 unique sequences from 12481 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg018_S201_L001_R1_001.fastq
## Encountered 4173 unique sequences from 18766 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg019_S202_L001_R1_001.fastq
## Encountered 3954 unique sequences from 16055 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bi001_S203_L001_R1_001.fastq
## Encountered 4028 unique sequences from 17384 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bi002_S204_L001_R1_001.fastq
## Encountered 4085 unique sequences from 19912 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bi003_S205_L001_R1_001.fastq
## Encountered 2940 unique sequences from 12910 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bi004_S206_L001_R1_001.fastq
## Encountered 6901 unique sequences from 42207 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bi005_S207_L001_R1_001.fastq
## Encountered 42 unique sequences from 111 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bi006_S208_L001_R1_001.fastq
## Encountered 7463 unique sequences from 38312 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bi007_S209_L001_R1_001.fastq
## Encountered 6608 unique sequences from 30085 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-CKC0001_S210_L001_R1_001.fastq
## Encountered 1793 unique sequences from 9923 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ESE0004_S211_L001_R1_001.fastq
## Encountered 3591 unique sequences from 11887 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-20230909_S212_L001_R1_001.fastq
## Encountered 18 unique sequences from 33 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-20230923_S213_L001_R1_001.fastq
## Encountered 1 unique sequences from 1 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-20230924_S214_L001_R1_001.fastq
## Encountered 5 unique sequences from 5 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-20231007_S215_L001_R1_001.fastq
## Encountered 3 unique sequences from 3 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-20231008_S216_L001_R1_001.fastq
## Encountered 11 unique sequences from 50 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-20231009_S217_L001_R1_001.fastq
## Encountered 89 unique sequences from 358 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-2024220A_S218_L001_R1_001.fastq
## Encountered 59 unique sequences from 131 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-2024220B_S219_L001_R1_001.fastq
## Encountered 50 unique sequences from 129 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-2024221A_S220_L001_R1_001.fastq
## Encountered 60 unique sequences from 159 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-2024221B_S221_L001_R1_001.fastq
## Encountered 57 unique sequences from 130 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-2024222A_S222_L001_R1_001.fastq
## Encountered 56 unique sequences from 88 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-2024222B_S223_L001_R1_001.fastq
## Encountered 16 unique sequences from 76 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-2024312A_S224_L001_R1_001.fastq
## Encountered 42 unique sequences from 104 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-2024312B_S225_L001_R1_001.fastq
## Encountered 14 unique sequences from 28 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-2024314A_S226_L001_R1_001.fastq
## Encountered 1 unique sequences from 1 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-2024319_S228_L001_R1_001.fastq
## Encountered 6 unique sequences from 6 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-2024320_S229_L001_R1_001.fastq
## Encountered 14 unique sequences from 21 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0007_S230_L001_R1_001.fastq
## Encountered 1549 unique sequences from 4798 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0027_S232_L001_R1_001.fastq
## Encountered 1367 unique sequences from 5767 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0044_S233_L001_R1_001.fastq
## Encountered 2375 unique sequences from 8955 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0045_S234_L001_R1_001.fastq
## Encountered 1735 unique sequences from 6222 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0052_S235_L001_R1_001.fastq
## Encountered 1671 unique sequences from 5529 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0054_S236_L001_R1_001.fastq
## Encountered 2838 unique sequences from 16389 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0055_S237_L001_R1_001.fastq
## Encountered 2381 unique sequences from 15797 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0071_S238_L001_R1_001.fastq
## Encountered 3053 unique sequences from 11709 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0095_S239_L001_R1_001.fastq
## Encountered 1744 unique sequences from 8701 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0096_S240_L001_R1_001.fastq
## Encountered 3288 unique sequences from 14500 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0105_S241_L001_R1_001.fastq
## Encountered 2875 unique sequences from 19463 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0106_S242_L001_R1_001.fastq
## Encountered 1697 unique sequences from 5682 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0119_S243_L001_R1_001.fastq
## Encountered 3772 unique sequences from 12665 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0134_S244_L001_R1_001.fastq
## Encountered 2561 unique sequences from 11447 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0135_S245_L001_R1_001.fastq
## Encountered 2014 unique sequences from 8081 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0136_S246_L001_R1_001.fastq
## Encountered 874 unique sequences from 2509 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0137_S247_L001_R1_001.fastq
## Encountered 1570 unique sequences from 4076 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0138_S248_L001_R1_001.fastq
## Encountered 1459 unique sequences from 6754 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0139_S249_L001_R1_001.fastq
## Encountered 2528 unique sequences from 10020 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0150_S250_L001_R1_001.fastq
## Encountered 3695 unique sequences from 18611 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0153_S251_L001_R1_001.fastq
## Encountered 1396 unique sequences from 4536 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0155_S252_L001_R1_001.fastq
## Encountered 3534 unique sequences from 17599 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0156_S253_L001_R1_001.fastq
## Encountered 2899 unique sequences from 12671 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0159_S254_L001_R1_001.fastq
## Encountered 2257 unique sequences from 9988 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0163_S255_L001_R1_001.fastq
## Encountered 2567 unique sequences from 9958 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0165_S256_L001_R1_001.fastq
## Encountered 3012 unique sequences from 12110 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0167_S257_L001_R1_001.fastq
## Encountered 2650 unique sequences from 9019 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0168_S258_L001_R1_001.fastq
## Encountered 1809 unique sequences from 7722 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0169_S259_L001_R1_001.fastq
## Encountered 2530 unique sequences from 8051 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0170_S260_L001_R1_001.fastq
## Encountered 2997 unique sequences from 9209 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0200_S261_L001_R1_001.fastq
## Encountered 1628 unique sequences from 8381 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0201_S262_L001_R1_001.fastq
## Encountered 7103 unique sequences from 26461 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0205_S263_L001_R1_001.fastq
## Encountered 2735 unique sequences from 8493 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0209_S264_L001_R1_001.fastq
## Encountered 3356 unique sequences from 14812 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0221_S265_L001_R1_001.fastq
## Encountered 4243 unique sequences from 20667 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0224_S266_L001_R1_001.fastq
## Encountered 1922 unique sequences from 5175 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0225_S267_L001_R1_001.fastq
## Encountered 2717 unique sequences from 11502 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0227_S268_L001_R1_001.fastq
## Encountered 2383 unique sequences from 11615 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0241_S269_L001_R1_001.fastq
## Encountered 1827 unique sequences from 10364 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0244_S270_L001_R1_001.fastq
## Encountered 1098 unique sequences from 2924 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0246_S271_L001_R1_001.fastq
## Encountered 1639 unique sequences from 4743 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0248_S272_L001_R1_001.fastq
## Encountered 1900 unique sequences from 9660 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0253_S273_L001_R1_001.fastq
## Encountered 1963 unique sequences from 6275 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0254_S274_L001_R1_001.fastq
## Encountered 4974 unique sequences from 22985 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0256_S231_L001_R1_001.fastq
## Encountered 2012 unique sequences from 7938 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0259_S275_L001_R1_001.fastq
## Encountered 3905 unique sequences from 19483 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0263_S276_L001_R1_001.fastq
## Encountered 2845 unique sequences from 11532 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0272_S278_L001_R1_001.fastq
## Encountered 3381 unique sequences from 12275 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-pcr-its2-neg-ctrl-20231021-20231119_S279_L001_R1_001.fastq
## Encountered 7 unique sequences from 7 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-pcr-its2-neg-ctrl-20231022-20231120_S280_L001_R1_001.fastq
## Encountered 1 unique sequences from 1 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-pcr-its2-neg-ctrl-20231023_S281_L001_R1_001.fastq
## Encountered 8 unique sequences from 12 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-pcr-its2-neg-ctrl-20240411_S282_L001_R1_001.fastq
## Encountered 5 unique sequences from 5 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-pcr-its2-neg-ctrl-20240417_S284_L001_R1_001.fastq
## Encountered 110 unique sequences from 260 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-pcr-its2-neg-ctrl-20240418A_S285_L001_R1_001.fastq
## Encountered 103 unique sequences from 309 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-pcr-its2-neg-ctrl-20240418B_S286_L001_R1_001.fastq
## Encountered 32 unique sequences from 61 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-pcr-its2-neg-ctrl-20240517_S287_L001_R1_001.fastq
## Encountered 10 unique sequences from 33 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-pcr-its2-neg-ctrl-20240524_S288_L001_R1_001.fastq
## Encountered 1 unique sequences from 2 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-pcr-its2-neg-ctrl-Saskia-20240411_S289_L001_R1_001.fastq
## Encountered 2 unique sequences from 2 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-SCA0009_S290_L001_R1_001.fastq
## Encountered 3854 unique sequences from 12498 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-SCA0010_S291_L001_R1_001.fastq
## Encountered 3950 unique sequences from 13374 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-SCA0013_S292_L001_R1_001.fastq
## Encountered 2230 unique sequences from 6844 total sequences read.
derepRs <- derepFastq(filtRs, verbose = TRUE)
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-16-H1_S31_L001_R2_001.fastq
## Encountered 2 unique sequences from 2 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-16-H5_S32_L001_R2_001.fastq
## Encountered 3 unique sequences from 3 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-16-H6_S33_L001_R2_001.fastq
## Encountered 1 unique sequences from 1 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-17-H2_S34_L001_R2_001.fastq
## Encountered 7 unique sequences from 7 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-17-H4_S35_L001_R2_001.fastq
## Encountered 8 unique sequences from 8 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-17-H8_S36_L001_R2_001.fastq
## Encountered 5 unique sequences from 5 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-18-H3_S37_L001_R2_001.fastq
## Encountered 20651 unique sequences from 28544 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-18-H7_S38_L001_R2_001.fastq
## Encountered 9292 unique sequences from 14114 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-18-H9_S39_L001_R2_001.fastq
## Encountered 8987 unique sequences from 9775 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-3-H1_S40_L001_R2_001.fastq
## Encountered 12234 unique sequences from 17562 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-3-H5_S41_L001_R2_001.fastq
## Encountered 12653 unique sequences from 17183 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-3-H6_S42_L001_R2_001.fastq
## Encountered 7680 unique sequences from 9113 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-30-H1_S43_L001_R2_001.fastq
## Encountered 8576 unique sequences from 11400 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-30-H6_S45_L001_R2_001.fastq
## Encountered 1 unique sequences from 1 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-4-H2_S46_L001_R2_001.fastq
## Encountered 3775 unique sequences from 3807 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-4-H4_S47_L001_R2_001.fastq
## Encountered 6335 unique sequences from 7207 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-4-H8_S48_L001_R2_001.fastq
## Encountered 14856 unique sequences from 20412 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-5-H3_S49_L001_R2_001.fastq
## Encountered 9488 unique sequences from 13330 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-5-H7_S50_L001_R2_001.fastq
## Encountered 9633 unique sequences from 13763 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-5-H9_S51_L001_R2_001.fastq
## Encountered 2 unique sequences from 2 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-7-1-H2_S52_L001_R2_001.fastq
## Encountered 1 unique sequences from 1 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-7-1-H4_S53_L001_R2_001.fastq
## Encountered 3 unique sequences from 3 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-7-1-H8_S54_L001_R2_001.fastq
## Encountered 37458 unique sequences from 59663 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-7-14-H1_S55_L001_R2_001.fastq
## Encountered 52 unique sequences from 54 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-7-14-H5_S56_L001_R2_001.fastq
## Encountered 21493 unique sequences from 25171 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-7-14-H6_S57_L001_R2_001.fastq
## Encountered 18015 unique sequences from 25820 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-7-15-H4_S59_L001_R2_001.fastq
## Encountered 4 unique sequences from 4 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-7-15-H8_S60_L001_R2_001.fastq
## Encountered 3 unique sequences from 3 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-7-16-H3_S61_L001_R2_001.fastq
## Encountered 4 unique sequences from 4 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-7-16-H9_S63_L001_R2_001.fastq
## Encountered 2 unique sequences from 2 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-7-2-H3_S64_L001_R2_001.fastq
## Encountered 13885 unique sequences from 19284 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-7-2-H7_S65_L001_R2_001.fastq
## Encountered 11100 unique sequences from 14455 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-7-2-H9_S66_L001_R2_001.fastq
## Encountered 5723 unique sequences from 7696 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-13-H1_S67_L001_R2_001.fastq
## Encountered 18255 unique sequences from 33662 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-13-H3_S68_L001_R2_001.fastq
## Encountered 13414 unique sequences from 19584 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-14-H11_S69_L001_R2_001.fastq
## Encountered 17392 unique sequences from 30473 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-14-H6_S70_L001_R2_001.fastq
## Encountered 15131 unique sequences from 21451 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-14-H7_S71_L001_R2_001.fastq
## Encountered 15157 unique sequences from 27667 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-15-H8_S72_L001_R2_001.fastq
## Encountered 18315 unique sequences from 29183 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-21-H10_S73_L001_R2_001.fastq
## Encountered 16215 unique sequences from 22468 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-21-H12_S74_L001_R2_001.fastq
## Encountered 9976 unique sequences from 15386 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-21-H9_S75_L001_R2_001.fastq
## Encountered 16545 unique sequences from 22706 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-27-H21_S76_L001_R2_001.fastq
## Encountered 10501 unique sequences from 13598 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-27-H22_S77_L001_R2_001.fastq
## Encountered 9094 unique sequences from 16586 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-27-H27_S78_L001_R2_001.fastq
## Encountered 8284 unique sequences from 11031 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-28-H25_S79_L001_R2_001.fastq
## Encountered 23005 unique sequences from 37109 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-28-H26_S80_L001_R2_001.fastq
## Encountered 14602 unique sequences from 18011 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-28-H28_S81_L001_R2_001.fastq
## Encountered 19816 unique sequences from 24520 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-29-H17_S82_L001_R2_001.fastq
## Encountered 14096 unique sequences from 20380 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-29-H23_S83_L001_R2_001.fastq
## Encountered 10484 unique sequences from 15119 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-29-H24_S84_L001_R2_001.fastq
## Encountered 14554 unique sequences from 23804 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-4-H21_S85_L001_R2_001.fastq
## Encountered 7481 unique sequences from 7846 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-4-H22_S86_L001_R2_001.fastq
## Encountered 25806 unique sequences from 32343 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-4-H27_S87_L001_R2_001.fastq
## Encountered 4201 unique sequences from 4382 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-5-H18_S88_L001_R2_001.fastq
## Encountered 7890 unique sequences from 8700 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-5-H25_S89_L001_R2_001.fastq
## Encountered 5707 unique sequences from 6167 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-5-H26_S90_L001_R2_001.fastq
## Encountered 21761 unique sequences from 30751 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-6-H17_S91_L001_R2_001.fastq
## Encountered 8981 unique sequences from 9885 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-6-H24_S92_L001_R2_001.fastq
## Encountered 20131 unique sequences from 27479 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-7-H23_S93_L001_R2_001.fastq
## Encountered 10106 unique sequences from 10700 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-7-14-H10_S94_L001_R2_001.fastq
## Encountered 12430 unique sequences from 17609 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-7-20-H27_S96_L001_R2_001.fastq
## Encountered 10588 unique sequences from 12038 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-7-21-H25_S97_L001_R2_001.fastq
## Encountered 9763 unique sequences from 16172 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-7-21-H26_S98_L001_R2_001.fastq
## Encountered 6 unique sequences from 6 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-7-21-H28_S99_L001_R2_001.fastq
## Encountered 2 unique sequences from 2 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-7-6-H11_S100_L001_R2_001.fastq
## Encountered 16302 unique sequences from 23260 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-7-6-H30_S101_L001_R2_001.fastq
## Encountered 1 unique sequences from 1 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-7-6-H6_S102_L001_R2_001.fastq
## Encountered 9380 unique sequences from 12438 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-7-7-H8_S104_L001_R2_001.fastq
## Encountered 12352 unique sequences from 23534 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-7-8-H3_S105_L001_R2_001.fastq
## Encountered 13309 unique sequences from 23041 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-12-H3_S106_L001_R2_001.fastq
## Encountered 8624 unique sequences from 12263 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-12-H5_S107_L001_R2_001.fastq
## Encountered 17396 unique sequences from 24829 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-12-H7_S108_L001_R2_001.fastq
## Encountered 5638 unique sequences from 6086 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-13-H6_S109_L001_R2_001.fastq
## Encountered 9379 unique sequences from 13625 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-13-H8_S110_L001_R2_001.fastq
## Encountered 11650 unique sequences from 15490 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-13-H9_S111_L001_R2_001.fastq
## Encountered 12010 unique sequences from 19503 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-14-H3_S112_L001_R2_001.fastq
## Encountered 13041 unique sequences from 20699 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-14-H7_S113_L001_R2_001.fastq
## Encountered 21643 unique sequences from 33188 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-14-H9_S114_L001_R2_001.fastq
## Encountered 22444 unique sequences from 37485 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-16-H5_S115_L001_R2_001.fastq
## Encountered 13802 unique sequences from 15022 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-24-H6_S116_L001_R2_001.fastq
## Encountered 26469 unique sequences from 34675 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-24-H8_S117_L001_R2_001.fastq
## Encountered 13441 unique sequences from 17439 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-25-H2_S118_L001_R2_001.fastq
## Encountered 23138 unique sequences from 31265 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-25-H4_S119_L001_R2_001.fastq
## Encountered 22363 unique sequences from 31537 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-26-H1_S120_L001_R2_001.fastq
## Encountered 6823 unique sequences from 8136 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-26-H7_S121_L001_R2_001.fastq
## Encountered 18833 unique sequences from 24821 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-27-H3_S122_L001_R2_001.fastq
## Encountered 7990 unique sequences from 10606 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-27-H5_S123_L001_R2_001.fastq
## Encountered 12619 unique sequences from 16479 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-8-H1_S124_L001_R2_001.fastq
## Encountered 14780 unique sequences from 21254 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-8-H2_S125_L001_R2_001.fastq
## Encountered 9264 unique sequences from 16527 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-8-H4_S126_L001_R2_001.fastq
## Encountered 23279 unique sequences from 38333 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-9-H2_S127_L001_R2_001.fastq
## Encountered 10008 unique sequences from 14590 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-9-H4_S128_L001_R2_001.fastq
## Encountered 14492 unique sequences from 22545 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-15-H6_S129_L001_R2_001.fastq
## Encountered 19089 unique sequences from 23983 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-16-H4_S130_L001_R2_001.fastq
## Encountered 24471 unique sequences from 29295 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-17-H1_S131_L001_R2_001.fastq
## Encountered 12485 unique sequences from 14894 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-18-H3_S132_L001_R2_001.fastq
## Encountered 15401 unique sequences from 21650 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-18-H7_S133_L001_R2_001.fastq
## Encountered 10946 unique sequences from 12527 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-29-H5_S134_L001_R2_001.fastq
## Encountered 18471 unique sequences from 25406 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-29-H7_S135_L001_R2_001.fastq
## Encountered 23929 unique sequences from 40098 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-30-H8_S136_L001_R2_001.fastq
## Encountered 17741 unique sequences from 27389 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-30-H9_S137_L001_R2_001.fastq
## Encountered 30297 unique sequences from 42773 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-5-H1_S138_L001_R2_001.fastq
## Encountered 10825 unique sequences from 18663 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-5-H2_S139_L001_R2_001.fastq
## Encountered 16829 unique sequences from 24683 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-5-H4_S140_L001_R2_001.fastq
## Encountered 12554 unique sequences from 16886 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-6-H6_S141_L001_R2_001.fastq
## Encountered 16740 unique sequences from 23320 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-6-H8_S142_L001_R2_001.fastq
## Encountered 18169 unique sequences from 25858 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-6-H9_S143_L001_R2_001.fastq
## Encountered 24915 unique sequences from 37973 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-8-H3_S144_L001_R2_001.fastq
## Encountered 10851 unique sequences from 14762 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-8-H5_S145_L001_R2_001.fastq
## Encountered 13001 unique sequences from 16132 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-8-H7_S146_L001_R2_001.fastq
## Encountered 18245 unique sequences from 24378 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-8-4-H2_S147_L001_R2_001.fastq
## Encountered 14175 unique sequences from 23680 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-8-4-H5_S148_L001_R2_001.fastq
## Encountered 25007 unique sequences from 34917 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-8-4-H6_S149_L001_R2_001.fastq
## Encountered 12933 unique sequences from 15791 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-8-4-H7_S150_L001_R2_001.fastq
## Encountered 15802 unique sequences from 19770 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-8-4-H8_S151_L001_R2_001.fastq
## Encountered 12828 unique sequences from 17643 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-8-4-H9_S152_L001_R2_001.fastq
## Encountered 10897 unique sequences from 14039 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Ba001_S153_L001_R2_001.fastq
## Encountered 9564 unique sequences from 10777 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Ba002_S154_L001_R2_001.fastq
## Encountered 4555 unique sequences from 5537 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Ba003_S155_L001_R2_001.fastq
## Encountered 8468 unique sequences from 9074 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb001_S156_L001_R2_001.fastq
## Encountered 5272 unique sequences from 6275 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb002_S157_L001_R2_001.fastq
## Encountered 6020 unique sequences from 7357 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb003_S158_L001_R2_001.fastq
## Encountered 9127 unique sequences from 11309 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb004_S159_L001_R2_001.fastq
## Encountered 8578 unique sequences from 10220 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb005_S160_L001_R2_001.fastq
## Encountered 4481 unique sequences from 5421 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb007_S161_L001_R2_001.fastq
## Encountered 896 unique sequences from 1227 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb008_S162_L001_R2_001.fastq
## Encountered 2604 unique sequences from 3419 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb009_S163_L001_R2_001.fastq
## Encountered 1601 unique sequences from 2193 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb010_S164_L001_R2_001.fastq
## Encountered 8187 unique sequences from 8989 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb011_S165_L001_R2_001.fastq
## Encountered 4100 unique sequences from 5075 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb012_S166_L001_R2_001.fastq
## Encountered 11477 unique sequences from 15928 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb013_S167_L001_R2_001.fastq
## Encountered 5391 unique sequences from 6123 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb014_S168_L001_R2_001.fastq
## Encountered 2729 unique sequences from 3127 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb015_S169_L001_R2_001.fastq
## Encountered 2477 unique sequences from 3045 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb016_S170_L001_R2_001.fastq
## Encountered 291 unique sequences from 318 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb017_S171_L001_R2_001.fastq
## Encountered 1751 unique sequences from 2279 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb018_S172_L001_R2_001.fastq
## Encountered 4355 unique sequences from 5380 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb019_S173_L001_R2_001.fastq
## Encountered 6953 unique sequences from 8859 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb020_S174_L001_R2_001.fastq
## Encountered 5238 unique sequences from 6218 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb021_S175_L001_R2_001.fastq
## Encountered 12357 unique sequences from 13981 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb022_S176_L001_R2_001.fastq
## Encountered 17515 unique sequences from 24593 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb023_S177_L001_R2_001.fastq
## Encountered 19635 unique sequences from 24923 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb024_S178_L001_R2_001.fastq
## Encountered 20105 unique sequences from 36400 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb025_S179_L001_R2_001.fastq
## Encountered 11672 unique sequences from 16550 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bf001_S180_L001_R2_001.fastq
## Encountered 18751 unique sequences from 22204 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bf002_S181_L001_R2_001.fastq
## Encountered 13171 unique sequences from 18314 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bf003_S182_L001_R2_001.fastq
## Encountered 21411 unique sequences from 28486 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bf004_S183_L001_R2_001.fastq
## Encountered 16159 unique sequences from 20792 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg001_S184_L001_R2_001.fastq
## Encountered 15587 unique sequences from 19460 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg002_S185_L001_R2_001.fastq
## Encountered 11341 unique sequences from 14410 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg003_S186_L001_R2_001.fastq
## Encountered 21400 unique sequences from 31643 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg004_S187_L001_R2_001.fastq
## Encountered 17754 unique sequences from 21133 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg005_S188_L001_R2_001.fastq
## Encountered 13224 unique sequences from 18459 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg006_S189_L001_R2_001.fastq
## Encountered 24845 unique sequences from 30218 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg007_S190_L001_R2_001.fastq
## Encountered 12445 unique sequences from 14612 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg008_S191_L001_R2_001.fastq
## Encountered 8847 unique sequences from 12218 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg009_S192_L001_R2_001.fastq
## Encountered 15726 unique sequences from 21107 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg010_S193_L001_R2_001.fastq
## Encountered 22838 unique sequences from 35028 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg011_S194_L001_R2_001.fastq
## Encountered 17841 unique sequences from 25569 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg012_S195_L001_R2_001.fastq
## Encountered 21094 unique sequences from 32557 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg013_S196_L001_R2_001.fastq
## Encountered 10647 unique sequences from 11893 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg014_S197_L001_R2_001.fastq
## Encountered 20211 unique sequences from 23693 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg015_S198_L001_R2_001.fastq
## Encountered 12558 unique sequences from 17641 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg016_S199_L001_R2_001.fastq
## Encountered 9333 unique sequences from 15525 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg017_S200_L001_R2_001.fastq
## Encountered 8808 unique sequences from 12481 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg018_S201_L001_R2_001.fastq
## Encountered 12539 unique sequences from 18766 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg019_S202_L001_R2_001.fastq
## Encountered 11658 unique sequences from 16055 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bi001_S203_L001_R2_001.fastq
## Encountered 12252 unique sequences from 17384 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bi002_S204_L001_R2_001.fastq
## Encountered 13277 unique sequences from 19912 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bi003_S205_L001_R2_001.fastq
## Encountered 9690 unique sequences from 12910 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bi004_S206_L001_R2_001.fastq
## Encountered 24844 unique sequences from 42207 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bi005_S207_L001_R2_001.fastq
## Encountered 91 unique sequences from 111 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bi006_S208_L001_R2_001.fastq
## Encountered 23958 unique sequences from 38312 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bi007_S209_L001_R2_001.fastq
## Encountered 20075 unique sequences from 30085 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-CKC0001_S210_L001_R2_001.fastq
## Encountered 7973 unique sequences from 9923 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ESE0004_S211_L001_R2_001.fastq
## Encountered 10449 unique sequences from 11887 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-20230909_S212_L001_R2_001.fastq
## Encountered 26 unique sequences from 33 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-20230923_S213_L001_R2_001.fastq
## Encountered 1 unique sequences from 1 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-20230924_S214_L001_R2_001.fastq
## Encountered 5 unique sequences from 5 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-20231007_S215_L001_R2_001.fastq
## Encountered 3 unique sequences from 3 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-20231008_S216_L001_R2_001.fastq
## Encountered 44 unique sequences from 50 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-20231009_S217_L001_R2_001.fastq
## Encountered 269 unique sequences from 358 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-2024220A_S218_L001_R2_001.fastq
## Encountered 125 unique sequences from 131 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-2024220B_S219_L001_R2_001.fastq
## Encountered 128 unique sequences from 129 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-2024221A_S220_L001_R2_001.fastq
## Encountered 145 unique sequences from 159 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-2024221B_S221_L001_R2_001.fastq
## Encountered 121 unique sequences from 130 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-2024222A_S222_L001_R2_001.fastq
## Encountered 86 unique sequences from 88 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-2024222B_S223_L001_R2_001.fastq
## Encountered 59 unique sequences from 76 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-2024312A_S224_L001_R2_001.fastq
## Encountered 90 unique sequences from 104 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-2024312B_S225_L001_R2_001.fastq
## Encountered 28 unique sequences from 28 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-2024314A_S226_L001_R2_001.fastq
## Encountered 1 unique sequences from 1 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-2024319_S228_L001_R2_001.fastq
## Encountered 6 unique sequences from 6 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-2024320_S229_L001_R2_001.fastq
## Encountered 21 unique sequences from 21 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0007_S230_L001_R2_001.fastq
## Encountered 4301 unique sequences from 4798 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0027_S232_L001_R2_001.fastq
## Encountered 5132 unique sequences from 5767 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0044_S233_L001_R2_001.fastq
## Encountered 7465 unique sequences from 8955 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0045_S234_L001_R2_001.fastq
## Encountered 5338 unique sequences from 6222 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0052_S235_L001_R2_001.fastq
## Encountered 5040 unique sequences from 5529 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0054_S236_L001_R2_001.fastq
## Encountered 12714 unique sequences from 16389 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0055_S237_L001_R2_001.fastq
## Encountered 11946 unique sequences from 15797 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0071_S238_L001_R2_001.fastq
## Encountered 9645 unique sequences from 11709 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0095_S239_L001_R2_001.fastq
## Encountered 7498 unique sequences from 8701 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0096_S240_L001_R2_001.fastq
## Encountered 9745 unique sequences from 14500 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0105_S241_L001_R2_001.fastq
## Encountered 12394 unique sequences from 19463 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0106_S242_L001_R2_001.fastq
## Encountered 4264 unique sequences from 5682 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0119_S243_L001_R2_001.fastq
## Encountered 10207 unique sequences from 12665 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0134_S244_L001_R2_001.fastq
## Encountered 9902 unique sequences from 11447 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0135_S245_L001_R2_001.fastq
## Encountered 7059 unique sequences from 8081 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0136_S246_L001_R2_001.fastq
## Encountered 2327 unique sequences from 2509 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0137_S247_L001_R2_001.fastq
## Encountered 3709 unique sequences from 4076 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0138_S248_L001_R2_001.fastq
## Encountered 5876 unique sequences from 6754 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0139_S249_L001_R2_001.fastq
## Encountered 8067 unique sequences from 10020 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0150_S250_L001_R2_001.fastq
## Encountered 11523 unique sequences from 18611 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0153_S251_L001_R2_001.fastq
## Encountered 3556 unique sequences from 4536 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0155_S252_L001_R2_001.fastq
## Encountered 13498 unique sequences from 17599 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0156_S253_L001_R2_001.fastq
## Encountered 10678 unique sequences from 12671 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0159_S254_L001_R2_001.fastq
## Encountered 6936 unique sequences from 9988 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0163_S255_L001_R2_001.fastq
## Encountered 7361 unique sequences from 9958 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0165_S256_L001_R2_001.fastq
## Encountered 8797 unique sequences from 12110 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0167_S257_L001_R2_001.fastq
## Encountered 6907 unique sequences from 9019 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0168_S258_L001_R2_001.fastq
## Encountered 5774 unique sequences from 7722 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0169_S259_L001_R2_001.fastq
## Encountered 7066 unique sequences from 8051 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0170_S260_L001_R2_001.fastq
## Encountered 8283 unique sequences from 9209 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0200_S261_L001_R2_001.fastq
## Encountered 7229 unique sequences from 8381 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0201_S262_L001_R2_001.fastq
## Encountered 20095 unique sequences from 26461 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0205_S263_L001_R2_001.fastq
## Encountered 7010 unique sequences from 8493 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0209_S264_L001_R2_001.fastq
## Encountered 11058 unique sequences from 14812 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0221_S265_L001_R2_001.fastq
## Encountered 12556 unique sequences from 20667 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0224_S266_L001_R2_001.fastq
## Encountered 4743 unique sequences from 5175 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0225_S267_L001_R2_001.fastq
## Encountered 9339 unique sequences from 11502 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0227_S268_L001_R2_001.fastq
## Encountered 9988 unique sequences from 11615 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0241_S269_L001_R2_001.fastq
## Encountered 7863 unique sequences from 10364 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0244_S270_L001_R2_001.fastq
## Encountered 2637 unique sequences from 2924 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0246_S271_L001_R2_001.fastq
## Encountered 4251 unique sequences from 4743 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0248_S272_L001_R2_001.fastq
## Encountered 8025 unique sequences from 9660 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0253_S273_L001_R2_001.fastq
## Encountered 5779 unique sequences from 6275 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0254_S274_L001_R2_001.fastq
## Encountered 15009 unique sequences from 22985 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0256_S231_L001_R2_001.fastq
## Encountered 5578 unique sequences from 7938 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0259_S275_L001_R2_001.fastq
## Encountered 16271 unique sequences from 19483 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0263_S276_L001_R2_001.fastq
## Encountered 9682 unique sequences from 11532 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0272_S278_L001_R2_001.fastq
## Encountered 8832 unique sequences from 12275 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-pcr-its2-neg-ctrl-20231021-20231119_S279_L001_R2_001.fastq
## Encountered 7 unique sequences from 7 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-pcr-its2-neg-ctrl-20231022-20231120_S280_L001_R2_001.fastq
## Encountered 1 unique sequences from 1 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-pcr-its2-neg-ctrl-20231023_S281_L001_R2_001.fastq
## Encountered 12 unique sequences from 12 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-pcr-its2-neg-ctrl-20240411_S282_L001_R2_001.fastq
## Encountered 5 unique sequences from 5 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-pcr-its2-neg-ctrl-20240417_S284_L001_R2_001.fastq
## Encountered 252 unique sequences from 260 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-pcr-its2-neg-ctrl-20240418A_S285_L001_R2_001.fastq
## Encountered 261 unique sequences from 309 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-pcr-its2-neg-ctrl-20240418B_S286_L001_R2_001.fastq
## Encountered 50 unique sequences from 61 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-pcr-its2-neg-ctrl-20240517_S287_L001_R2_001.fastq
## Encountered 33 unique sequences from 33 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-pcr-its2-neg-ctrl-20240524_S288_L001_R2_001.fastq
## Encountered 2 unique sequences from 2 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-pcr-its2-neg-ctrl-Saskia-20240411_S289_L001_R2_001.fastq
## Encountered 2 unique sequences from 2 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-SCA0009_S290_L001_R2_001.fastq
## Encountered 10987 unique sequences from 12498 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-SCA0010_S291_L001_R2_001.fastq
## Encountered 11855 unique sequences from 13374 total sequences read.
## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-SCA0013_S292_L001_R2_001.fastq
## Encountered 6161 unique sequences from 6844 total sequences read.
#Note that the dereplicated sequences only exist in the R environment, and are not saved into a separate output subdirectory

Updating sample names (after samples drop out)

Extract sample names from filtF (to only include samples that passed the previous filter)

# my file names have 'junk' at the beginning and end of the file name
                  basename(filtFs[241])
## [1] "ITS2-KLS0272_S278_L001_R1_001.fastq"
         strsplit(basename(filtFs[241]),"_S")
## [[1]]
## [1] "ITS2-KLS0272"          "278_L001_R1_001.fastq"
         strsplit(basename(filtFs[241]),"_S")[[1]][1]
## [1] "ITS2-KLS0272"
strsplit(strsplit(basename(filtFs[241]),"_S")[[1]][1],"-")[[1]]
## [1] "ITS2"    "KLS0272"
# and their structure (esp length) differs between worker samples, queen samples, extraction negative controls, and pcr negative controls. 
paste(strsplit(strsplit(basename(filtFs[241]),"_S")[[1]][1],"-")[[1]][-1],collapse="_")
## [1] "KLS0272"
paste(strsplit(strsplit(basename(filtFs[226]),"_S")[[1]][1],"-")[[1]][-1],collapse="_")
## [1] "KLS0205"
paste(strsplit(strsplit(basename(filtFs[176]),"_S")[[1]][1],"-")[[1]][-1],collapse="_")
## [1] "ESE0004"
paste(strsplit(strsplit(basename(filtFs[1]),  "_S")[[1]][1],"-")[[1]][-1],collapse="_")
## [1] "2020_6_16_H1"
# make a simple function to replicate above
get.sample.name <- function(fname) paste(strsplit(strsplit(basename(fname[1]),  "_S")[[1]][1],"-")[[1]][-1],collapse="_")

sample.names <- unname(sapply(filtFs, get.sample.name))
head(sample.names)
## [1] "2020_6_16_H1" "2020_6_16_H5" "2020_6_16_H6" "2020_6_17_H2" "2020_6_17_H4"
## [6] "2020_6_17_H8"
length(sample.names)
## [1] 254
# Name the dereplicated class objects by the sample names
names(derepFs) <- sample.names
names(derepRs) <- sample.names

##Denoise reads to resolve exact sequences with dada2

At this step, the core sample inference algorithm is applied to the dereplicated sequences from /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered (remember that the dereplicated sequences only exist in the R environment)

DADA2 infers sample sequences exactly and resolves differences of as little as 1 nucleotide using the models of the error rates we learned in the previous step

dadaFs <- dada(derepFs, err = errF, multithread = TRUE)
## Sample 1 - 2 reads in 2 unique sequences.
## Sample 2 - 3 reads in 3 unique sequences.
## Sample 3 - 1 reads in 1 unique sequences.
## Sample 4 - 7 reads in 7 unique sequences.
## Sample 5 - 8 reads in 8 unique sequences.
## Sample 6 - 5 reads in 5 unique sequences.
## Sample 7 - 28544 reads in 6411 unique sequences.
## Sample 8 - 14114 reads in 3101 unique sequences.
## Sample 9 - 9775 reads in 2768 unique sequences.
## Sample 10 - 17562 reads in 4015 unique sequences.
## Sample 11 - 17183 reads in 3747 unique sequences.
## Sample 12 - 9113 reads in 2460 unique sequences.
## Sample 13 - 11400 reads in 3335 unique sequences.
## Sample 14 - 1 reads in 1 unique sequences.
## Sample 15 - 3807 reads in 1627 unique sequences.
## Sample 16 - 7207 reads in 2493 unique sequences.
## Sample 17 - 20412 reads in 4403 unique sequences.
## Sample 18 - 13330 reads in 3161 unique sequences.
## Sample 19 - 13763 reads in 3277 unique sequences.
## Sample 20 - 2 reads in 2 unique sequences.
## Sample 21 - 1 reads in 1 unique sequences.
## Sample 22 - 3 reads in 3 unique sequences.
## Sample 23 - 59663 reads in 8478 unique sequences.
## Sample 24 - 54 reads in 24 unique sequences.
## Sample 25 - 25171 reads in 6274 unique sequences.
## Sample 26 - 25820 reads in 5803 unique sequences.
## Sample 27 - 4 reads in 4 unique sequences.
## Sample 28 - 3 reads in 3 unique sequences.
## Sample 29 - 4 reads in 4 unique sequences.
## Sample 30 - 2 reads in 2 unique sequences.
## Sample 31 - 19284 reads in 5547 unique sequences.
## Sample 32 - 14455 reads in 4022 unique sequences.
## Sample 33 - 7696 reads in 2140 unique sequences.
## Sample 34 - 33662 reads in 5141 unique sequences.
## Sample 35 - 19584 reads in 4338 unique sequences.
## Sample 36 - 30473 reads in 5338 unique sequences.
## Sample 37 - 21451 reads in 4070 unique sequences.
## Sample 38 - 27667 reads in 4454 unique sequences.
## Sample 39 - 29183 reads in 5768 unique sequences.
## Sample 40 - 22468 reads in 4572 unique sequences.
## Sample 41 - 15386 reads in 2949 unique sequences.
## Sample 42 - 22706 reads in 4394 unique sequences.
## Sample 43 - 13598 reads in 3341 unique sequences.
## Sample 44 - 16586 reads in 2965 unique sequences.
## Sample 45 - 11031 reads in 2829 unique sequences.
## Sample 46 - 37109 reads in 6110 unique sequences.
## Sample 47 - 18011 reads in 4087 unique sequences.
## Sample 48 - 24520 reads in 7181 unique sequences.
## Sample 49 - 20380 reads in 4809 unique sequences.
## Sample 50 - 15119 reads in 3259 unique sequences.
## Sample 51 - 23804 reads in 4177 unique sequences.
## Sample 52 - 7846 reads in 2410 unique sequences.
## Sample 53 - 32343 reads in 5726 unique sequences.
## Sample 54 - 4382 reads in 1388 unique sequences.
## Sample 55 - 8700 reads in 2268 unique sequences.
## Sample 56 - 6167 reads in 1757 unique sequences.
## Sample 57 - 30751 reads in 6992 unique sequences.
## Sample 58 - 9885 reads in 2556 unique sequences.
## Sample 59 - 27479 reads in 5879 unique sequences.
## Sample 60 - 10700 reads in 2630 unique sequences.
## Sample 61 - 17609 reads in 2867 unique sequences.
## Sample 62 - 12038 reads in 3138 unique sequences.
## Sample 63 - 16172 reads in 3041 unique sequences.
## Sample 64 - 6 reads in 6 unique sequences.
## Sample 65 - 2 reads in 2 unique sequences.
## Sample 66 - 23260 reads in 6533 unique sequences.
## Sample 67 - 1 reads in 1 unique sequences.
## Sample 68 - 12438 reads in 3537 unique sequences.
## Sample 69 - 23534 reads in 3627 unique sequences.
## Sample 70 - 23041 reads in 4064 unique sequences.
## Sample 71 - 12263 reads in 2883 unique sequences.
## Sample 72 - 24829 reads in 4865 unique sequences.
## Sample 73 - 6086 reads in 1895 unique sequences.
## Sample 74 - 13625 reads in 2828 unique sequences.
## Sample 75 - 15490 reads in 3772 unique sequences.
## Sample 76 - 19503 reads in 3407 unique sequences.
## Sample 77 - 20699 reads in 3942 unique sequences.
## Sample 78 - 33188 reads in 6335 unique sequences.
## Sample 79 - 37485 reads in 6508 unique sequences.
## Sample 80 - 15022 reads in 3705 unique sequences.
## Sample 81 - 34675 reads in 7751 unique sequences.
## Sample 82 - 17439 reads in 4903 unique sequences.
## Sample 83 - 31265 reads in 7986 unique sequences.
## Sample 84 - 31537 reads in 6969 unique sequences.
## Sample 85 - 8136 reads in 3225 unique sequences.
## Sample 86 - 24821 reads in 5999 unique sequences.
## Sample 87 - 10606 reads in 2902 unique sequences.
## Sample 88 - 16479 reads in 4567 unique sequences.
## Sample 89 - 21254 reads in 5088 unique sequences.
## Sample 90 - 16527 reads in 3050 unique sequences.
## Sample 91 - 38333 reads in 5349 unique sequences.
## Sample 92 - 14590 reads in 3228 unique sequences.
## Sample 93 - 22545 reads in 4381 unique sequences.
## Sample 94 - 23983 reads in 5373 unique sequences.
## Sample 95 - 29295 reads in 5533 unique sequences.
## Sample 96 - 14894 reads in 3654 unique sequences.
## Sample 97 - 21650 reads in 5279 unique sequences.
## Sample 98 - 12527 reads in 2367 unique sequences.
## Sample 99 - 25406 reads in 5393 unique sequences.
## Sample 100 - 40098 reads in 7171 unique sequences.
## Sample 101 - 27389 reads in 5008 unique sequences.
## Sample 102 - 42773 reads in 7051 unique sequences.
## Sample 103 - 18663 reads in 3099 unique sequences.
## Sample 104 - 24683 reads in 3874 unique sequences.
## Sample 105 - 16886 reads in 2963 unique sequences.
## Sample 106 - 23320 reads in 3889 unique sequences.
## Sample 107 - 25858 reads in 4410 unique sequences.
## Sample 108 - 37973 reads in 6979 unique sequences.
## Sample 109 - 14762 reads in 2995 unique sequences.
## Sample 110 - 16132 reads in 2382 unique sequences.
## Sample 111 - 24378 reads in 4194 unique sequences.
## Sample 112 - 23680 reads in 3737 unique sequences.
## Sample 113 - 34917 reads in 7584 unique sequences.
## Sample 114 - 15791 reads in 3819 unique sequences.
## Sample 115 - 19770 reads in 5292 unique sequences.
## Sample 116 - 17643 reads in 4401 unique sequences.
## Sample 117 - 14039 reads in 4314 unique sequences.
## Sample 118 - 10777 reads in 3129 unique sequences.
## Sample 119 - 5537 reads in 1886 unique sequences.
## Sample 120 - 9074 reads in 3998 unique sequences.
## Sample 121 - 6275 reads in 1888 unique sequences.
## Sample 122 - 7357 reads in 2159 unique sequences.
## Sample 123 - 11309 reads in 3197 unique sequences.
## Sample 124 - 10220 reads in 3109 unique sequences.
## Sample 125 - 5421 reads in 1556 unique sequences.
## Sample 126 - 1227 reads in 309 unique sequences.
## Sample 127 - 3419 reads in 884 unique sequences.
## Sample 128 - 2193 reads in 585 unique sequences.
## Sample 129 - 8989 reads in 3182 unique sequences.
## Sample 130 - 5075 reads in 1819 unique sequences.
## Sample 131 - 15928 reads in 3718 unique sequences.
## Sample 132 - 6123 reads in 2077 unique sequences.
## Sample 133 - 3127 reads in 1087 unique sequences.
## Sample 134 - 3045 reads in 1103 unique sequences.
## Sample 135 - 318 reads in 124 unique sequences.
## Sample 136 - 2279 reads in 742 unique sequences.
## Sample 137 - 5380 reads in 2031 unique sequences.
## Sample 138 - 8859 reads in 2438 unique sequences.
## Sample 139 - 6218 reads in 1302 unique sequences.
## Sample 140 - 13981 reads in 4100 unique sequences.
## Sample 141 - 24593 reads in 5105 unique sequences.
## Sample 142 - 24923 reads in 4617 unique sequences.
## Sample 143 - 36400 reads in 5541 unique sequences.
## Sample 144 - 16550 reads in 3804 unique sequences.
## Sample 145 - 22204 reads in 3964 unique sequences.
## Sample 146 - 18314 reads in 3447 unique sequences.
## Sample 147 - 28486 reads in 4327 unique sequences.
## Sample 148 - 20792 reads in 4943 unique sequences.
## Sample 149 - 19460 reads in 5227 unique sequences.
## Sample 150 - 14410 reads in 4239 unique sequences.
## Sample 151 - 31643 reads in 7289 unique sequences.
## Sample 152 - 21133 reads in 6501 unique sequences.
## Sample 153 - 18459 reads in 4026 unique sequences.
## Sample 154 - 30218 reads in 7585 unique sequences.
## Sample 155 - 14612 reads in 3071 unique sequences.
## Sample 156 - 12218 reads in 3225 unique sequences.
## Sample 157 - 21107 reads in 5073 unique sequences.
## Sample 158 - 35028 reads in 7453 unique sequences.
## Sample 159 - 25569 reads in 5894 unique sequences.
## Sample 160 - 32557 reads in 6000 unique sequences.
## Sample 161 - 11893 reads in 2861 unique sequences.
## Sample 162 - 23693 reads in 3897 unique sequences.
## Sample 163 - 17641 reads in 3853 unique sequences.
## Sample 164 - 15525 reads in 2884 unique sequences.
## Sample 165 - 12481 reads in 3301 unique sequences.
## Sample 166 - 18766 reads in 4173 unique sequences.
## Sample 167 - 16055 reads in 3954 unique sequences.
## Sample 168 - 17384 reads in 4028 unique sequences.
## Sample 169 - 19912 reads in 4085 unique sequences.
## Sample 170 - 12910 reads in 2940 unique sequences.
## Sample 171 - 42207 reads in 6901 unique sequences.
## Sample 172 - 111 reads in 42 unique sequences.
## Sample 173 - 38312 reads in 7463 unique sequences.
## Sample 174 - 30085 reads in 6608 unique sequences.
## Sample 175 - 9923 reads in 1793 unique sequences.
## Sample 176 - 11887 reads in 3591 unique sequences.
## Sample 177 - 33 reads in 18 unique sequences.
## Sample 178 - 1 reads in 1 unique sequences.
## Sample 179 - 5 reads in 5 unique sequences.
## Sample 180 - 3 reads in 3 unique sequences.
## Sample 181 - 50 reads in 11 unique sequences.
## Sample 182 - 358 reads in 89 unique sequences.
## Sample 183 - 131 reads in 59 unique sequences.
## Sample 184 - 129 reads in 50 unique sequences.
## Sample 185 - 159 reads in 60 unique sequences.
## Sample 186 - 130 reads in 57 unique sequences.
## Sample 187 - 88 reads in 56 unique sequences.
## Sample 188 - 76 reads in 16 unique sequences.
## Sample 189 - 104 reads in 42 unique sequences.
## Sample 190 - 28 reads in 14 unique sequences.
## Sample 191 - 1 reads in 1 unique sequences.
## Sample 192 - 6 reads in 6 unique sequences.
## Sample 193 - 21 reads in 14 unique sequences.
## Sample 194 - 4798 reads in 1549 unique sequences.
## Sample 195 - 5767 reads in 1367 unique sequences.
## Sample 196 - 8955 reads in 2375 unique sequences.
## Sample 197 - 6222 reads in 1735 unique sequences.
## Sample 198 - 5529 reads in 1671 unique sequences.
## Sample 199 - 16389 reads in 2838 unique sequences.
## Sample 200 - 15797 reads in 2381 unique sequences.
## Sample 201 - 11709 reads in 3053 unique sequences.
## Sample 202 - 8701 reads in 1744 unique sequences.
## Sample 203 - 14500 reads in 3288 unique sequences.
## Sample 204 - 19463 reads in 2875 unique sequences.
## Sample 205 - 5682 reads in 1697 unique sequences.
## Sample 206 - 12665 reads in 3772 unique sequences.
## Sample 207 - 11447 reads in 2561 unique sequences.
## Sample 208 - 8081 reads in 2014 unique sequences.
## Sample 209 - 2509 reads in 874 unique sequences.
## Sample 210 - 4076 reads in 1570 unique sequences.
## Sample 211 - 6754 reads in 1459 unique sequences.
## Sample 212 - 10020 reads in 2528 unique sequences.
## Sample 213 - 18611 reads in 3695 unique sequences.
## Sample 214 - 4536 reads in 1396 unique sequences.
## Sample 215 - 17599 reads in 3534 unique sequences.
## Sample 216 - 12671 reads in 2899 unique sequences.
## Sample 217 - 9988 reads in 2257 unique sequences.
## Sample 218 - 9958 reads in 2567 unique sequences.
## Sample 219 - 12110 reads in 3012 unique sequences.
## Sample 220 - 9019 reads in 2650 unique sequences.
## Sample 221 - 7722 reads in 1809 unique sequences.
## Sample 222 - 8051 reads in 2530 unique sequences.
## Sample 223 - 9209 reads in 2997 unique sequences.
## Sample 224 - 8381 reads in 1628 unique sequences.
## Sample 225 - 26461 reads in 7103 unique sequences.
## Sample 226 - 8493 reads in 2735 unique sequences.
## Sample 227 - 14812 reads in 3356 unique sequences.
## Sample 228 - 20667 reads in 4243 unique sequences.
## Sample 229 - 5175 reads in 1922 unique sequences.
## Sample 230 - 11502 reads in 2717 unique sequences.
## Sample 231 - 11615 reads in 2383 unique sequences.
## Sample 232 - 10364 reads in 1827 unique sequences.
## Sample 233 - 2924 reads in 1098 unique sequences.
## Sample 234 - 4743 reads in 1639 unique sequences.
## Sample 235 - 9660 reads in 1900 unique sequences.
## Sample 236 - 6275 reads in 1963 unique sequences.
## Sample 237 - 22985 reads in 4974 unique sequences.
## Sample 238 - 7938 reads in 2012 unique sequences.
## Sample 239 - 19483 reads in 3905 unique sequences.
## Sample 240 - 11532 reads in 2845 unique sequences.
## Sample 241 - 12275 reads in 3381 unique sequences.
## Sample 242 - 7 reads in 7 unique sequences.
## Sample 243 - 1 reads in 1 unique sequences.
## Sample 244 - 12 reads in 8 unique sequences.
## Sample 245 - 5 reads in 5 unique sequences.
## Sample 246 - 260 reads in 110 unique sequences.
## Sample 247 - 309 reads in 103 unique sequences.
## Sample 248 - 61 reads in 32 unique sequences.
## Sample 249 - 33 reads in 10 unique sequences.
## Sample 250 - 2 reads in 1 unique sequences.
## Sample 251 - 2 reads in 2 unique sequences.
## Sample 252 - 12498 reads in 3854 unique sequences.
## Sample 253 - 13374 reads in 3950 unique sequences.
## Sample 254 - 6844 reads in 2230 unique sequences.
dadaRs <- dada(derepRs, err = errR, multithread = TRUE)
## Sample 1 - 2 reads in 2 unique sequences.
## Sample 2 - 3 reads in 3 unique sequences.
## Sample 3 - 1 reads in 1 unique sequences.
## Sample 4 - 7 reads in 7 unique sequences.
## Sample 5 - 8 reads in 8 unique sequences.
## Sample 6 - 5 reads in 5 unique sequences.
## Sample 7 - 28544 reads in 20651 unique sequences.
## Sample 8 - 14114 reads in 9292 unique sequences.
## Sample 9 - 9775 reads in 8987 unique sequences.
## Sample 10 - 17562 reads in 12234 unique sequences.
## Sample 11 - 17183 reads in 12653 unique sequences.
## Sample 12 - 9113 reads in 7680 unique sequences.
## Sample 13 - 11400 reads in 8576 unique sequences.
## Sample 14 - 1 reads in 1 unique sequences.
## Sample 15 - 3807 reads in 3775 unique sequences.
## Sample 16 - 7207 reads in 6335 unique sequences.
## Sample 17 - 20412 reads in 14856 unique sequences.
## Sample 18 - 13330 reads in 9488 unique sequences.
## Sample 19 - 13763 reads in 9633 unique sequences.
## Sample 20 - 2 reads in 2 unique sequences.
## Sample 21 - 1 reads in 1 unique sequences.
## Sample 22 - 3 reads in 3 unique sequences.
## Sample 23 - 59663 reads in 37458 unique sequences.
## Sample 24 - 54 reads in 52 unique sequences.
## Sample 25 - 25171 reads in 21493 unique sequences.
## Sample 26 - 25820 reads in 18015 unique sequences.
## Sample 27 - 4 reads in 4 unique sequences.
## Sample 28 - 3 reads in 3 unique sequences.
## Sample 29 - 4 reads in 4 unique sequences.
## Sample 30 - 2 reads in 2 unique sequences.
## Sample 31 - 19284 reads in 13885 unique sequences.
## Sample 32 - 14455 reads in 11100 unique sequences.
## Sample 33 - 7696 reads in 5723 unique sequences.
## Sample 34 - 33662 reads in 18255 unique sequences.
## Sample 35 - 19584 reads in 13414 unique sequences.
## Sample 36 - 30473 reads in 17392 unique sequences.
## Sample 37 - 21451 reads in 15131 unique sequences.
## Sample 38 - 27667 reads in 15157 unique sequences.
## Sample 39 - 29183 reads in 18315 unique sequences.
## Sample 40 - 22468 reads in 16215 unique sequences.
## Sample 41 - 15386 reads in 9976 unique sequences.
## Sample 42 - 22706 reads in 16545 unique sequences.
## Sample 43 - 13598 reads in 10501 unique sequences.
## Sample 44 - 16586 reads in 9094 unique sequences.
## Sample 45 - 11031 reads in 8284 unique sequences.
## Sample 46 - 37109 reads in 23005 unique sequences.
## Sample 47 - 18011 reads in 14602 unique sequences.
## Sample 48 - 24520 reads in 19816 unique sequences.
## Sample 49 - 20380 reads in 14096 unique sequences.
## Sample 50 - 15119 reads in 10484 unique sequences.
## Sample 51 - 23804 reads in 14554 unique sequences.
## Sample 52 - 7846 reads in 7481 unique sequences.
## Sample 53 - 32343 reads in 25806 unique sequences.
## Sample 54 - 4382 reads in 4201 unique sequences.
## Sample 55 - 8700 reads in 7890 unique sequences.
## Sample 56 - 6167 reads in 5707 unique sequences.
## Sample 57 - 30751 reads in 21761 unique sequences.
## Sample 58 - 9885 reads in 8981 unique sequences.
## Sample 59 - 27479 reads in 20131 unique sequences.
## Sample 60 - 10700 reads in 10106 unique sequences.
## Sample 61 - 17609 reads in 12430 unique sequences.
## Sample 62 - 12038 reads in 10588 unique sequences.
## Sample 63 - 16172 reads in 9763 unique sequences.
## Sample 64 - 6 reads in 6 unique sequences.
## Sample 65 - 2 reads in 2 unique sequences.
## Sample 66 - 23260 reads in 16302 unique sequences.
## Sample 67 - 1 reads in 1 unique sequences.
## Sample 68 - 12438 reads in 9380 unique sequences.
## Sample 69 - 23534 reads in 12352 unique sequences.
## Sample 70 - 23041 reads in 13309 unique sequences.
## Sample 71 - 12263 reads in 8624 unique sequences.
## Sample 72 - 24829 reads in 17396 unique sequences.
## Sample 73 - 6086 reads in 5638 unique sequences.
## Sample 74 - 13625 reads in 9379 unique sequences.
## Sample 75 - 15490 reads in 11650 unique sequences.
## Sample 76 - 19503 reads in 12010 unique sequences.
## Sample 77 - 20699 reads in 13041 unique sequences.
## Sample 78 - 33188 reads in 21643 unique sequences.
## Sample 79 - 37485 reads in 22444 unique sequences.
## Sample 80 - 15022 reads in 13802 unique sequences.
## Sample 81 - 34675 reads in 26469 unique sequences.
## Sample 82 - 17439 reads in 13441 unique sequences.
## Sample 83 - 31265 reads in 23138 unique sequences.
## Sample 84 - 31537 reads in 22363 unique sequences.
## Sample 85 - 8136 reads in 6823 unique sequences.
## Sample 86 - 24821 reads in 18833 unique sequences.
## Sample 87 - 10606 reads in 7990 unique sequences.
## Sample 88 - 16479 reads in 12619 unique sequences.
## Sample 89 - 21254 reads in 14780 unique sequences.
## Sample 90 - 16527 reads in 9264 unique sequences.
## Sample 91 - 38333 reads in 23279 unique sequences.
## Sample 92 - 14590 reads in 10008 unique sequences.
## Sample 93 - 22545 reads in 14492 unique sequences.
## Sample 94 - 23983 reads in 19089 unique sequences.
## Sample 95 - 29295 reads in 24471 unique sequences.
## Sample 96 - 14894 reads in 12485 unique sequences.
## Sample 97 - 21650 reads in 15401 unique sequences.
## Sample 98 - 12527 reads in 10946 unique sequences.
## Sample 99 - 25406 reads in 18471 unique sequences.
## Sample 100 - 40098 reads in 23929 unique sequences.
## Sample 101 - 27389 reads in 17741 unique sequences.
## Sample 102 - 42773 reads in 30297 unique sequences.
## Sample 103 - 18663 reads in 10825 unique sequences.
## Sample 104 - 24683 reads in 16829 unique sequences.
## Sample 105 - 16886 reads in 12554 unique sequences.
## Sample 106 - 23320 reads in 16740 unique sequences.
## Sample 107 - 25858 reads in 18169 unique sequences.
## Sample 108 - 37973 reads in 24915 unique sequences.
## Sample 109 - 14762 reads in 10851 unique sequences.
## Sample 110 - 16132 reads in 13001 unique sequences.
## Sample 111 - 24378 reads in 18245 unique sequences.
## Sample 112 - 23680 reads in 14175 unique sequences.
## Sample 113 - 34917 reads in 25007 unique sequences.
## Sample 114 - 15791 reads in 12933 unique sequences.
## Sample 115 - 19770 reads in 15802 unique sequences.
## Sample 116 - 17643 reads in 12828 unique sequences.
## Sample 117 - 14039 reads in 10897 unique sequences.
## Sample 118 - 10777 reads in 9564 unique sequences.
## Sample 119 - 5537 reads in 4555 unique sequences.
## Sample 120 - 9074 reads in 8468 unique sequences.
## Sample 121 - 6275 reads in 5272 unique sequences.
## Sample 122 - 7357 reads in 6020 unique sequences.
## Sample 123 - 11309 reads in 9127 unique sequences.
## Sample 124 - 10220 reads in 8578 unique sequences.
## Sample 125 - 5421 reads in 4481 unique sequences.
## Sample 126 - 1227 reads in 896 unique sequences.
## Sample 127 - 3419 reads in 2604 unique sequences.
## Sample 128 - 2193 reads in 1601 unique sequences.
## Sample 129 - 8989 reads in 8187 unique sequences.
## Sample 130 - 5075 reads in 4100 unique sequences.
## Sample 131 - 15928 reads in 11477 unique sequences.
## Sample 132 - 6123 reads in 5391 unique sequences.
## Sample 133 - 3127 reads in 2729 unique sequences.
## Sample 134 - 3045 reads in 2477 unique sequences.
## Sample 135 - 318 reads in 291 unique sequences.
## Sample 136 - 2279 reads in 1751 unique sequences.
## Sample 137 - 5380 reads in 4355 unique sequences.
## Sample 138 - 8859 reads in 6953 unique sequences.
## Sample 139 - 6218 reads in 5238 unique sequences.
## Sample 140 - 13981 reads in 12357 unique sequences.
## Sample 141 - 24593 reads in 17515 unique sequences.
## Sample 142 - 24923 reads in 19635 unique sequences.
## Sample 143 - 36400 reads in 20105 unique sequences.
## Sample 144 - 16550 reads in 11672 unique sequences.
## Sample 145 - 22204 reads in 18751 unique sequences.
## Sample 146 - 18314 reads in 13171 unique sequences.
## Sample 147 - 28486 reads in 21411 unique sequences.
## Sample 148 - 20792 reads in 16159 unique sequences.
## Sample 149 - 19460 reads in 15587 unique sequences.
## Sample 150 - 14410 reads in 11341 unique sequences.
## Sample 151 - 31643 reads in 21400 unique sequences.
## Sample 152 - 21133 reads in 17754 unique sequences.
## Sample 153 - 18459 reads in 13224 unique sequences.
## Sample 154 - 30218 reads in 24845 unique sequences.
## Sample 155 - 14612 reads in 12445 unique sequences.
## Sample 156 - 12218 reads in 8847 unique sequences.
## Sample 157 - 21107 reads in 15726 unique sequences.
## Sample 158 - 35028 reads in 22838 unique sequences.
## Sample 159 - 25569 reads in 17841 unique sequences.
## Sample 160 - 32557 reads in 21094 unique sequences.
## Sample 161 - 11893 reads in 10647 unique sequences.
## Sample 162 - 23693 reads in 20211 unique sequences.
## Sample 163 - 17641 reads in 12558 unique sequences.
## Sample 164 - 15525 reads in 9333 unique sequences.
## Sample 165 - 12481 reads in 8808 unique sequences.
## Sample 166 - 18766 reads in 12539 unique sequences.
## Sample 167 - 16055 reads in 11658 unique sequences.
## Sample 168 - 17384 reads in 12252 unique sequences.
## Sample 169 - 19912 reads in 13277 unique sequences.
## Sample 170 - 12910 reads in 9690 unique sequences.
## Sample 171 - 42207 reads in 24844 unique sequences.
## Sample 172 - 111 reads in 91 unique sequences.
## Sample 173 - 38312 reads in 23958 unique sequences.
## Sample 174 - 30085 reads in 20075 unique sequences.
## Sample 175 - 9923 reads in 7973 unique sequences.
## Sample 176 - 11887 reads in 10449 unique sequences.
## Sample 177 - 33 reads in 26 unique sequences.
## Sample 178 - 1 reads in 1 unique sequences.
## Sample 179 - 5 reads in 5 unique sequences.
## Sample 180 - 3 reads in 3 unique sequences.
## Sample 181 - 50 reads in 44 unique sequences.
## Sample 182 - 358 reads in 269 unique sequences.
## Sample 183 - 131 reads in 125 unique sequences.
## Sample 184 - 129 reads in 128 unique sequences.
## Sample 185 - 159 reads in 145 unique sequences.
## Sample 186 - 130 reads in 121 unique sequences.
## Sample 187 - 88 reads in 86 unique sequences.
## Sample 188 - 76 reads in 59 unique sequences.
## Sample 189 - 104 reads in 90 unique sequences.
## Sample 190 - 28 reads in 28 unique sequences.
## Sample 191 - 1 reads in 1 unique sequences.
## Sample 192 - 6 reads in 6 unique sequences.
## Sample 193 - 21 reads in 21 unique sequences.
## Sample 194 - 4798 reads in 4301 unique sequences.
## Sample 195 - 5767 reads in 5132 unique sequences.
## Sample 196 - 8955 reads in 7465 unique sequences.
## Sample 197 - 6222 reads in 5338 unique sequences.
## Sample 198 - 5529 reads in 5040 unique sequences.
## Sample 199 - 16389 reads in 12714 unique sequences.
## Sample 200 - 15797 reads in 11946 unique sequences.
## Sample 201 - 11709 reads in 9645 unique sequences.
## Sample 202 - 8701 reads in 7498 unique sequences.
## Sample 203 - 14500 reads in 9745 unique sequences.
## Sample 204 - 19463 reads in 12394 unique sequences.
## Sample 205 - 5682 reads in 4264 unique sequences.
## Sample 206 - 12665 reads in 10207 unique sequences.
## Sample 207 - 11447 reads in 9902 unique sequences.
## Sample 208 - 8081 reads in 7059 unique sequences.
## Sample 209 - 2509 reads in 2327 unique sequences.
## Sample 210 - 4076 reads in 3709 unique sequences.
## Sample 211 - 6754 reads in 5876 unique sequences.
## Sample 212 - 10020 reads in 8067 unique sequences.
## Sample 213 - 18611 reads in 11523 unique sequences.
## Sample 214 - 4536 reads in 3556 unique sequences.
## Sample 215 - 17599 reads in 13498 unique sequences.
## Sample 216 - 12671 reads in 10678 unique sequences.
## Sample 217 - 9988 reads in 6936 unique sequences.
## Sample 218 - 9958 reads in 7361 unique sequences.
## Sample 219 - 12110 reads in 8797 unique sequences.
## Sample 220 - 9019 reads in 6907 unique sequences.
## Sample 221 - 7722 reads in 5774 unique sequences.
## Sample 222 - 8051 reads in 7066 unique sequences.
## Sample 223 - 9209 reads in 8283 unique sequences.
## Sample 224 - 8381 reads in 7229 unique sequences.
## Sample 225 - 26461 reads in 20095 unique sequences.
## Sample 226 - 8493 reads in 7010 unique sequences.
## Sample 227 - 14812 reads in 11058 unique sequences.
## Sample 228 - 20667 reads in 12556 unique sequences.
## Sample 229 - 5175 reads in 4743 unique sequences.
## Sample 230 - 11502 reads in 9339 unique sequences.
## Sample 231 - 11615 reads in 9988 unique sequences.
## Sample 232 - 10364 reads in 7863 unique sequences.
## Sample 233 - 2924 reads in 2637 unique sequences.
## Sample 234 - 4743 reads in 4251 unique sequences.
## Sample 235 - 9660 reads in 8025 unique sequences.
## Sample 236 - 6275 reads in 5779 unique sequences.
## Sample 237 - 22985 reads in 15009 unique sequences.
## Sample 238 - 7938 reads in 5578 unique sequences.
## Sample 239 - 19483 reads in 16271 unique sequences.
## Sample 240 - 11532 reads in 9682 unique sequences.
## Sample 241 - 12275 reads in 8832 unique sequences.
## Sample 242 - 7 reads in 7 unique sequences.
## Sample 243 - 1 reads in 1 unique sequences.
## Sample 244 - 12 reads in 12 unique sequences.
## Sample 245 - 5 reads in 5 unique sequences.
## Sample 246 - 260 reads in 252 unique sequences.
## Sample 247 - 309 reads in 261 unique sequences.
## Sample 248 - 61 reads in 50 unique sequences.
## Sample 249 - 33 reads in 33 unique sequences.
## Sample 250 - 2 reads in 2 unique sequences.
## Sample 251 - 2 reads in 2 unique sequences.
## Sample 252 - 12498 reads in 10987 unique sequences.
## Sample 253 - 13374 reads in 11855 unique sequences.
## Sample 254 - 6844 reads in 6161 unique sequences.

Merge paired reads

We’ve inferred the sample sequences in the forward and reverse reads independently. Now it’s time to merge those inferred sequences together, throwing out those pairs of reads that don’t match

mergers <- mergePairs(dadaFs, derepFs, dadaRs, derepRs, verbose=TRUE, minOverlap = 11, maxMismatch = 0)
## No paired-reads (in ZERO unique pairings) successfully merged out of 2 pairings) input.
## No paired-reads (in ZERO unique pairings) successfully merged out of 3 pairings) input.
## 1 paired-reads (in 1 unique pairings) successfully merged out of 1 (in 1 pairings) input.
## No paired-reads (in ZERO unique pairings) successfully merged out of 7 pairings) input.
## No paired-reads (in ZERO unique pairings) successfully merged out of 8 pairings) input.
## 0 paired-reads (in 0 unique pairings) successfully merged out of 1 (in 1 pairings) input.
## 12098 paired-reads (in 34 unique pairings) successfully merged out of 28223 (in 206 pairings) input.
## 6915 paired-reads (in 10 unique pairings) successfully merged out of 13914 (in 83 pairings) input.
## 6289 paired-reads (in 14 unique pairings) successfully merged out of 9549 (in 68 pairings) input.
## 11248 paired-reads (in 23 unique pairings) successfully merged out of 17279 (in 108 pairings) input.
## 5175 paired-reads (in 9 unique pairings) successfully merged out of 16402 (in 78 pairings) input.
## 4569 paired-reads (in 8 unique pairings) successfully merged out of 8843 (in 59 pairings) input.
## 7602 paired-reads (in 20 unique pairings) successfully merged out of 11094 (in 84 pairings) input.
## 0 paired-reads (in 0 unique pairings) successfully merged out of 1 (in 1 pairings) input.
## 523 paired-reads (in 2 unique pairings) successfully merged out of 3077 (in 28 pairings) input.
## 4726 paired-reads (in 13 unique pairings) successfully merged out of 6996 (in 65 pairings) input.
## 11122 paired-reads (in 26 unique pairings) successfully merged out of 19790 (in 116 pairings) input.
## 9082 paired-reads (in 20 unique pairings) successfully merged out of 13139 (in 94 pairings) input.
## 8180 paired-reads (in 21 unique pairings) successfully merged out of 13513 (in 103 pairings) input.
## No paired-reads (in ZERO unique pairings) successfully merged out of 2 pairings) input.
## 0 paired-reads (in 0 unique pairings) successfully merged out of 1 (in 1 pairings) input.
## 0 paired-reads (in 0 unique pairings) successfully merged out of 1 (in 1 pairings) input.
## 43369 paired-reads (in 52 unique pairings) successfully merged out of 59078 (in 369 pairings) input.
## 0 paired-reads (in 0 unique pairings) successfully merged out of 12 (in 1 pairings) input.
## 14971 paired-reads (in 23 unique pairings) successfully merged out of 24702 (in 144 pairings) input.
## 7418 paired-reads (in 18 unique pairings) successfully merged out of 25469 (in 177 pairings) input.
## 0 paired-reads (in 0 unique pairings) successfully merged out of 1 (in 1 pairings) input.
## No paired-reads (in ZERO unique pairings) successfully merged out of 3 pairings) input.
## No paired-reads (in ZERO unique pairings) successfully merged out of 4 pairings) input.
## No paired-reads (in ZERO unique pairings) successfully merged out of 2 pairings) input.
## 8781 paired-reads (in 27 unique pairings) successfully merged out of 18833 (in 174 pairings) input.
## 5466 paired-reads (in 15 unique pairings) successfully merged out of 14208 (in 106 pairings) input.
## 4279 paired-reads (in 12 unique pairings) successfully merged out of 7485 (in 51 pairings) input.
## 15660 paired-reads (in 17 unique pairings) successfully merged out of 33211 (in 146 pairings) input.
## 11578 paired-reads (in 23 unique pairings) successfully merged out of 19164 (in 156 pairings) input.
## 16707 paired-reads (in 28 unique pairings) successfully merged out of 30222 (in 214 pairings) input.
## 12751 paired-reads (in 22 unique pairings) successfully merged out of 20990 (in 125 pairings) input.
## 15278 paired-reads (in 15 unique pairings) successfully merged out of 27419 (in 153 pairings) input.
## 12859 paired-reads (in 14 unique pairings) successfully merged out of 28889 (in 183 pairings) input.
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## 7963 paired-reads (in 11 unique pairings) successfully merged out of 14806 (in 86 pairings) input.
## 9979 paired-reads (in 24 unique pairings) successfully merged out of 22382 (in 150 pairings) input.
## 3102 paired-reads (in 10 unique pairings) successfully merged out of 13375 (in 109 pairings) input.
## 7729 paired-reads (in 8 unique pairings) successfully merged out of 16037 (in 82 pairings) input.
## 4747 paired-reads (in 10 unique pairings) successfully merged out of 10843 (in 82 pairings) input.
## 21916 paired-reads (in 24 unique pairings) successfully merged out of 36924 (in 225 pairings) input.
## 14493 paired-reads (in 18 unique pairings) successfully merged out of 17755 (in 103 pairings) input.
## 15568 paired-reads (in 39 unique pairings) successfully merged out of 24236 (in 184 pairings) input.
## 10311 paired-reads (in 27 unique pairings) successfully merged out of 20098 (in 177 pairings) input.
## 6896 paired-reads (in 11 unique pairings) successfully merged out of 14883 (in 99 pairings) input.
## 12637 paired-reads (in 18 unique pairings) successfully merged out of 23495 (in 137 pairings) input.
## 3278 paired-reads (in 14 unique pairings) successfully merged out of 7539 (in 81 pairings) input.
## 24879 paired-reads (in 46 unique pairings) successfully merged out of 31504 (in 180 pairings) input.
## 2757 paired-reads (in 9 unique pairings) successfully merged out of 4258 (in 28 pairings) input.
## 5251 paired-reads (in 15 unique pairings) successfully merged out of 8456 (in 76 pairings) input.
## 3509 paired-reads (in 19 unique pairings) successfully merged out of 5978 (in 65 pairings) input.
## 21365 paired-reads (in 47 unique pairings) successfully merged out of 30337 (in 263 pairings) input.
## 6862 paired-reads (in 19 unique pairings) successfully merged out of 9275 (in 91 pairings) input.
## 16440 paired-reads (in 35 unique pairings) successfully merged out of 27100 (in 227 pairings) input.
## 5426 paired-reads (in 9 unique pairings) successfully merged out of 10508 (in 71 pairings) input.
## 10586 paired-reads (in 11 unique pairings) successfully merged out of 17469 (in 93 pairings) input.
## 6471 paired-reads (in 9 unique pairings) successfully merged out of 11850 (in 67 pairings) input.
## 7762 paired-reads (in 14 unique pairings) successfully merged out of 15996 (in 132 pairings) input.
## No paired-reads (in ZERO unique pairings) successfully merged out of 6 pairings) input.
## No paired-reads (in ZERO unique pairings) successfully merged out of 2 pairings) input.
## 13299 paired-reads (in 27 unique pairings) successfully merged out of 22660 (in 233 pairings) input.
## 0 paired-reads (in 0 unique pairings) successfully merged out of 1 (in 1 pairings) input.
## 8306 paired-reads (in 21 unique pairings) successfully merged out of 12156 (in 94 pairings) input.
## 11417 paired-reads (in 19 unique pairings) successfully merged out of 23417 (in 151 pairings) input.
## 13604 paired-reads (in 20 unique pairings) successfully merged out of 22949 (in 153 pairings) input.
## 562 paired-reads (in 5 unique pairings) successfully merged out of 11782 (in 68 pairings) input.
## 13128 paired-reads (in 18 unique pairings) successfully merged out of 24567 (in 191 pairings) input.
## 1110 paired-reads (in 9 unique pairings) successfully merged out of 5771 (in 42 pairings) input.
## 2698 paired-reads (in 6 unique pairings) successfully merged out of 13453 (in 74 pairings) input.
## 2908 paired-reads (in 15 unique pairings) successfully merged out of 15311 (in 127 pairings) input.
## 2064 paired-reads (in 6 unique pairings) successfully merged out of 19339 (in 89 pairings) input.
## 5256 paired-reads (in 17 unique pairings) successfully merged out of 20480 (in 153 pairings) input.
## 9490 paired-reads (in 25 unique pairings) successfully merged out of 32763 (in 215 pairings) input.
## 7580 paired-reads (in 24 unique pairings) successfully merged out of 37205 (in 255 pairings) input.
## 6672 paired-reads (in 16 unique pairings) successfully merged out of 14911 (in 108 pairings) input.
## 16009 paired-reads (in 44 unique pairings) successfully merged out of 34149 (in 299 pairings) input.
## 4635 paired-reads (in 20 unique pairings) successfully merged out of 16893 (in 124 pairings) input.
## 9531 paired-reads (in 22 unique pairings) successfully merged out of 30611 (in 276 pairings) input.
## 6982 paired-reads (in 26 unique pairings) successfully merged out of 31222 (in 256 pairings) input.
## 1635 paired-reads (in 7 unique pairings) successfully merged out of 7905 (in 74 pairings) input.
## 9736 paired-reads (in 27 unique pairings) successfully merged out of 24170 (in 181 pairings) input.
## 5163 paired-reads (in 12 unique pairings) successfully merged out of 10444 (in 96 pairings) input.
## 7162 paired-reads (in 20 unique pairings) successfully merged out of 15870 (in 132 pairings) input.
## 3934 paired-reads (in 11 unique pairings) successfully merged out of 21033 (in 111 pairings) input.
## 9485 paired-reads (in 12 unique pairings) successfully merged out of 16330 (in 94 pairings) input.
## 2996 paired-reads (in 5 unique pairings) successfully merged out of 38118 (in 177 pairings) input.
## 4780 paired-reads (in 16 unique pairings) successfully merged out of 14457 (in 89 pairings) input.
## 1051 paired-reads (in 7 unique pairings) successfully merged out of 22203 (in 106 pairings) input.
## 17240 paired-reads (in 31 unique pairings) successfully merged out of 23590 (in 151 pairings) input.
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## 15083 paired-reads (in 18 unique pairings) successfully merged out of 25217 (in 171 pairings) input.
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## 18773 paired-reads (in 18 unique pairings) successfully merged out of 27174 (in 151 pairings) input.
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## 19567 paired-reads (in 14 unique pairings) successfully merged out of 25416 (in 129 pairings) input.
## 29072 paired-reads (in 63 unique pairings) successfully merged out of 37532 (in 298 pairings) input.
## 8658 paired-reads (in 9 unique pairings) successfully merged out of 14614 (in 118 pairings) input.
## 8667 paired-reads (in 10 unique pairings) successfully merged out of 15915 (in 54 pairings) input.
## 16093 paired-reads (in 16 unique pairings) successfully merged out of 23861 (in 178 pairings) input.
## 14789 paired-reads (in 16 unique pairings) successfully merged out of 23251 (in 148 pairings) input.
## 24572 paired-reads (in 33 unique pairings) successfully merged out of 34565 (in 209 pairings) input.
## 7729 paired-reads (in 25 unique pairings) successfully merged out of 15286 (in 100 pairings) input.
## 12705 paired-reads (in 36 unique pairings) successfully merged out of 19303 (in 202 pairings) input.
## 13904 paired-reads (in 19 unique pairings) successfully merged out of 17420 (in 100 pairings) input.
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## 2744 paired-reads (in 7 unique pairings) successfully merged out of 6097 (in 53 pairings) input.
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## 805 paired-reads (in 3 unique pairings) successfully merged out of 1125 (in 10 pairings) input.
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## 1600 paired-reads (in 6 unique pairings) successfully merged out of 2139 (in 24 pairings) input.
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## 2232 paired-reads (in 6 unique pairings) successfully merged out of 4677 (in 35 pairings) input.
## 8121 paired-reads (in 22 unique pairings) successfully merged out of 15589 (in 172 pairings) input.
## 2009 paired-reads (in 11 unique pairings) successfully merged out of 5254 (in 39 pairings) input.
## 1185 paired-reads (in 2 unique pairings) successfully merged out of 2962 (in 20 pairings) input.
## 0 paired-reads (in 0 unique pairings) successfully merged out of 2818 (in 21 pairings) input.
## 105 paired-reads (in 2 unique pairings) successfully merged out of 301 (in 5 pairings) input.
## 1291 paired-reads (in 3 unique pairings) successfully merged out of 2186 (in 14 pairings) input.
## 1745 paired-reads (in 5 unique pairings) successfully merged out of 5049 (in 47 pairings) input.
## 6343 paired-reads (in 18 unique pairings) successfully merged out of 8478 (in 58 pairings) input.
## 0 paired-reads (in 0 unique pairings) successfully merged out of 5924 (in 12 pairings) input.
## 87 paired-reads (in 3 unique pairings) successfully merged out of 13222 (in 139 pairings) input.
## 11416 paired-reads (in 11 unique pairings) successfully merged out of 24075 (in 124 pairings) input.
## 7001 paired-reads (in 17 unique pairings) successfully merged out of 24391 (in 117 pairings) input.
## 1560 paired-reads (in 10 unique pairings) successfully merged out of 36117 (in 106 pairings) input.
## 6032 paired-reads (in 13 unique pairings) successfully merged out of 16252 (in 93 pairings) input.
## 5252 paired-reads (in 12 unique pairings) successfully merged out of 21879 (in 91 pairings) input.
## 535 paired-reads (in 7 unique pairings) successfully merged out of 18058 (in 100 pairings) input.
## 117 paired-reads (in 2 unique pairings) successfully merged out of 27863 (in 77 pairings) input.
## 839 paired-reads (in 8 unique pairings) successfully merged out of 20363 (in 102 pairings) input.
## 5403 paired-reads (in 20 unique pairings) successfully merged out of 18958 (in 137 pairings) input.
## 4965 paired-reads (in 15 unique pairings) successfully merged out of 13848 (in 118 pairings) input.
## 5273 paired-reads (in 18 unique pairings) successfully merged out of 30370 (in 170 pairings) input.
## 3256 paired-reads (in 22 unique pairings) successfully merged out of 20438 (in 160 pairings) input.
## 2314 paired-reads (in 8 unique pairings) successfully merged out of 18143 (in 86 pairings) input.
## 9699 paired-reads (in 20 unique pairings) successfully merged out of 29611 (in 231 pairings) input.
## 7078 paired-reads (in 18 unique pairings) successfully merged out of 14260 (in 94 pairings) input.
## 3054 paired-reads (in 7 unique pairings) successfully merged out of 11933 (in 72 pairings) input.
## 10561 paired-reads (in 18 unique pairings) successfully merged out of 20790 (in 150 pairings) input.
## 1418 paired-reads (in 14 unique pairings) successfully merged out of 34459 (in 213 pairings) input.
## 3272 paired-reads (in 22 unique pairings) successfully merged out of 24937 (in 170 pairings) input.
## 11465 paired-reads (in 16 unique pairings) successfully merged out of 32095 (in 154 pairings) input.
## 153 paired-reads (in 2 unique pairings) successfully merged out of 11373 (in 56 pairings) input.
## 8480 paired-reads (in 15 unique pairings) successfully merged out of 23320 (in 76 pairings) input.
## 5360 paired-reads (in 8 unique pairings) successfully merged out of 17234 (in 124 pairings) input.
## 11926 paired-reads (in 14 unique pairings) successfully merged out of 15245 (in 71 pairings) input.
## 6243 paired-reads (in 17 unique pairings) successfully merged out of 12181 (in 98 pairings) input.
## 10936 paired-reads (in 13 unique pairings) successfully merged out of 17960 (in 77 pairings) input.
## 7820 paired-reads (in 12 unique pairings) successfully merged out of 15748 (in 84 pairings) input.
## 7192 paired-reads (in 15 unique pairings) successfully merged out of 16965 (in 90 pairings) input.
## 2960 paired-reads (in 14 unique pairings) successfully merged out of 19527 (in 118 pairings) input.
## 4813 paired-reads (in 7 unique pairings) successfully merged out of 12736 (in 81 pairings) input.
## 2019 paired-reads (in 13 unique pairings) successfully merged out of 41792 (in 184 pairings) input.
## 0 paired-reads (in 0 unique pairings) successfully merged out of 96 (in 3 pairings) input.
## 3284 paired-reads (in 18 unique pairings) successfully merged out of 37790 (in 217 pairings) input.
## 18262 paired-reads (in 41 unique pairings) successfully merged out of 29409 (in 216 pairings) input.
## 7687 paired-reads (in 6 unique pairings) successfully merged out of 9784 (in 34 pairings) input.
## 2705 paired-reads (in 15 unique pairings) successfully merged out of 11508 (in 73 pairings) input.
## 20 paired-reads (in 2 unique pairings) successfully merged out of 20 (in 2 pairings) input.
## 1 paired-reads (in 1 unique pairings) successfully merged out of 1 (in 1 pairings) input.
## No paired-reads (in ZERO unique pairings) successfully merged out of 5 pairings) input.
## No paired-reads (in ZERO unique pairings) successfully merged out of 3 pairings) input.
## 36 paired-reads (in 1 unique pairings) successfully merged out of 48 (in 2 pairings) input.
## 272 paired-reads (in 2 unique pairings) successfully merged out of 332 (in 3 pairings) input.
## 44 paired-reads (in 2 unique pairings) successfully merged out of 48 (in 3 pairings) input.
## 0 paired-reads (in 0 unique pairings) successfully merged out of 22 (in 1 pairings) input.
## 0 paired-reads (in 0 unique pairings) successfully merged out of 44 (in 1 pairings) input.
## 9 paired-reads (in 1 unique pairings) successfully merged out of 74 (in 4 pairings) input.
## 0 paired-reads (in 0 unique pairings) successfully merged out of 5 (in 1 pairings) input.
## 54 paired-reads (in 1 unique pairings) successfully merged out of 54 (in 1 pairings) input.
## 49 paired-reads (in 1 unique pairings) successfully merged out of 49 (in 1 pairings) input.
## 0 paired-reads (in 0 unique pairings) successfully merged out of 4 (in 1 pairings) input.
## 1 paired-reads (in 1 unique pairings) successfully merged out of 1 (in 1 pairings) input.
## No paired-reads (in ZERO unique pairings) successfully merged out of 6 pairings) input.
## No paired-reads (in ZERO unique pairings) successfully merged out of 21 pairings) input.
## 2275 paired-reads (in 6 unique pairings) successfully merged out of 4704 (in 41 pairings) input.
## 101 paired-reads (in 1 unique pairings) successfully merged out of 5639 (in 13 pairings) input.
## 1298 paired-reads (in 6 unique pairings) successfully merged out of 8650 (in 46 pairings) input.
## 1656 paired-reads (in 6 unique pairings) successfully merged out of 6105 (in 38 pairings) input.
## 2470 paired-reads (in 5 unique pairings) successfully merged out of 5246 (in 50 pairings) input.
## 12626 paired-reads (in 7 unique pairings) successfully merged out of 16195 (in 44 pairings) input.
## 12197 paired-reads (in 9 unique pairings) successfully merged out of 15612 (in 51 pairings) input.
## 2782 paired-reads (in 5 unique pairings) successfully merged out of 11521 (in 59 pairings) input.
## 316 paired-reads (in 4 unique pairings) successfully merged out of 8333 (in 24 pairings) input.
## 6712 paired-reads (in 13 unique pairings) successfully merged out of 14204 (in 91 pairings) input.
## 15295 paired-reads (in 14 unique pairings) successfully merged out of 19253 (in 78 pairings) input.
## 1776 paired-reads (in 8 unique pairings) successfully merged out of 5459 (in 50 pairings) input.
## 1887 paired-reads (in 14 unique pairings) successfully merged out of 12243 (in 152 pairings) input.
## 3494 paired-reads (in 6 unique pairings) successfully merged out of 11101 (in 45 pairings) input.
## 2260 paired-reads (in 12 unique pairings) successfully merged out of 7762 (in 46 pairings) input.
## 7 paired-reads (in 1 unique pairings) successfully merged out of 1959 (in 10 pairings) input.
## 318 paired-reads (in 4 unique pairings) successfully merged out of 3762 (in 43 pairings) input.
## 1942 paired-reads (in 6 unique pairings) successfully merged out of 6514 (in 24 pairings) input.
## 733 paired-reads (in 6 unique pairings) successfully merged out of 9758 (in 67 pairings) input.
## 3122 paired-reads (in 8 unique pairings) successfully merged out of 18375 (in 87 pairings) input.
## 99 paired-reads (in 2 unique pairings) successfully merged out of 4351 (in 34 pairings) input.
## 126 paired-reads (in 4 unique pairings) successfully merged out of 17305 (in 70 pairings) input.
## 3975 paired-reads (in 5 unique pairings) successfully merged out of 12309 (in 44 pairings) input.
## 56 paired-reads (in 3 unique pairings) successfully merged out of 9555 (in 50 pairings) input.
## 1602 paired-reads (in 5 unique pairings) successfully merged out of 9846 (in 68 pairings) input.
## 1100 paired-reads (in 7 unique pairings) successfully merged out of 11711 (in 73 pairings) input.
## 4210 paired-reads (in 11 unique pairings) successfully merged out of 8690 (in 70 pairings) input.
## 1538 paired-reads (in 10 unique pairings) successfully merged out of 7602 (in 42 pairings) input.
## 340 paired-reads (in 5 unique pairings) successfully merged out of 7657 (in 57 pairings) input.
## 380 paired-reads (in 2 unique pairings) successfully merged out of 8916 (in 71 pairings) input.
## 257 paired-reads (in 5 unique pairings) successfully merged out of 8171 (in 38 pairings) input.
## 8746 paired-reads (in 17 unique pairings) successfully merged out of 25798 (in 168 pairings) input.
## 2235 paired-reads (in 7 unique pairings) successfully merged out of 8257 (in 37 pairings) input.
## 1675 paired-reads (in 11 unique pairings) successfully merged out of 14222 (in 80 pairings) input.
## 814 paired-reads (in 9 unique pairings) successfully merged out of 20171 (in 105 pairings) input.
## 598 paired-reads (in 6 unique pairings) successfully merged out of 4750 (in 45 pairings) input.
## 329 paired-reads (in 8 unique pairings) successfully merged out of 11107 (in 68 pairings) input.
## 495 paired-reads (in 7 unique pairings) successfully merged out of 11210 (in 49 pairings) input.
## 650 paired-reads (in 5 unique pairings) successfully merged out of 10187 (in 33 pairings) input.
## 123 paired-reads (in 2 unique pairings) successfully merged out of 2751 (in 36 pairings) input.
## 58 paired-reads (in 1 unique pairings) successfully merged out of 4468 (in 50 pairings) input.
## 4644 paired-reads (in 9 unique pairings) successfully merged out of 9436 (in 38 pairings) input.
## 771 paired-reads (in 6 unique pairings) successfully merged out of 5981 (in 59 pairings) input.
## 6498 paired-reads (in 16 unique pairings) successfully merged out of 22488 (in 149 pairings) input.
## 3898 paired-reads (in 7 unique pairings) successfully merged out of 7612 (in 50 pairings) input.
## 410 paired-reads (in 5 unique pairings) successfully merged out of 19035 (in 96 pairings) input.
## 91 paired-reads (in 1 unique pairings) successfully merged out of 11204 (in 86 pairings) input.
## 998 paired-reads (in 6 unique pairings) successfully merged out of 11969 (in 90 pairings) input.
## No paired-reads (in ZERO unique pairings) successfully merged out of 7 pairings) input.
## 0 paired-reads (in 0 unique pairings) successfully merged out of 1 (in 1 pairings) input.
## 0 paired-reads (in 0 unique pairings) successfully merged out of 5 (in 1 pairings) input.
## No paired-reads (in ZERO unique pairings) successfully merged out of 5 pairings) input.
## 0 paired-reads (in 0 unique pairings) successfully merged out of 39 (in 2 pairings) input.
## 107 paired-reads (in 5 unique pairings) successfully merged out of 247 (in 12 pairings) input.
## 28 paired-reads (in 1 unique pairings) successfully merged out of 28 (in 1 pairings) input.
## No paired-reads (in ZERO unique pairings) successfully merged out of 33 pairings) input.
## 0 paired-reads (in 0 unique pairings) successfully merged out of 2 (in 1 pairings) input.
## 0 paired-reads (in 0 unique pairings) successfully merged out of 2 (in 1 pairings) input.
## 597 paired-reads (in 7 unique pairings) successfully merged out of 12064 (in 136 pairings) input.
## 617 paired-reads (in 8 unique pairings) successfully merged out of 12739 (in 116 pairings) input.
## 459 paired-reads (in 6 unique pairings) successfully merged out of 6621 (in 81 pairings) input.
#this paper used min overlap of 10bp with "nrITS2": https://www.sciencedirect.com/science/article/pii/S0048969721055455#s0010

#I could play with minOverlap parameter to see the effects on merging
# length=30L; overlap=25; mismat=0
# mergers.test <- mergePairs(head(dadaFs, n=length), head(derepFs, n=length), head(dadaRs, n=length), head(derepRs, n=length), verbose=TRUE, minOverlap = overlap, maxMismatch = mismat)
# rm(length,overlap,mismat,mergers.test)

The mergePairs(…) function returns a data.frame corresponding to each successfully merged unique sequence. The “forward” and “reverse” columns record which forward and reverse sequence contributed to that merged sequence.

Construct ASV table

We can now construct an amplicon sequence variant table (ASV) table, a higher-resolution version of the OTU table produced by traditional methods.

seqtab <- makeSequenceTable(mergers)
dim(seqtab)
## [1]  254 1150
# 254 samples
# 1150 ASVs

#Post-dada2 quality control

Remove chimeras

A chimera is a single DNA sequence originating when multiple transcripts or DNA sequences get joined. Chimeras can be considered artifacts and be filtered out from the data during processing

The number of unique variants that are chimeras is higher in exact amplicon sequence variant (ASV) methods like DADA2 than they were in OTU methods, as chimeras very close to the real sequences are the most common type of chimera, and those used to be hidden by being lumped into an OTU. So some expectations based on previous OTU processing should be modified a little bit.

Robert Edgar discusses this in more detail in his uchime2 paper: https://doi.org/10.1101/074252

seqtab.nochim <- removeBimeraDenovo(seqtab, method="consensus", multithread=TRUE, verbose=TRUE) #more stringent parameter minFoldParentOverAbundance=2
## Identified 509 bimeras out of 1150 input sequences.
#Identified 509 bimeras out of 1150 input sequences.

length(sample.names)
## [1] 254
rownames(seqtab.nochim) <- sample.names

sum(seqtab) # reads
## [1] 1440920
sum(seqtab.nochim) # reads after removing chimeras
## [1] 1374531
sum(seqtab.nochim)/sum(seqtab) # proportion of reads remaining
## [1] 0.953926
100-((sum(seqtab.nochim)/sum(seqtab))*100) # percent of reads removed as chimeras
## [1] 4.607404

The more important metric here is the fraction of reads removed as bimeras, which is <20% here, so in the range of what we see. It is normal that a much higher fraction of ASVs than reads will be removed as bimeras, because chimeras are highly diverse but usually quite rare. You will see more chimeric ASVs if you sequence deeply, but not a meaningfully higher number of chimeric reads.

If you’re seeing more than 20% of reads being chimeric, you may want to re-examine your PCR protocol in the future. Longer extension times and fewer PCR cycles are both approaches that have been shown to reduce the formation of chimeric amplicons.

Inspect distribution of sequence lengths

Looking distribution of sequence lengths in the non-chimeric ASVs

table(nchar(getSequences(seqtab.nochim)))
## 
## 171 270 281 298 303 305 306 310 311 312 313 314 315 316 317 318 319 320 321 323 
##   1   2   1   1   1   1   1   2   4   4   5  11   4   7   4   4   1   1   1   1 
## 324 325 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 
##   2   1   6   2  11  19  17  18  26  13   3   1  38  13  10   1  35   1  17  18 
## 345 346 348 349 350 351 352 353 354 355 357 358 359 360 361 363 365 366 367 370 
##  28  72  46  32   9  23   3  25  10   1  14   7   1   2  13   8   9   1  11   1 
## 371 373 377 387 490 
##   2   4   1   2   7
sum(table(nchar(getSequences(seqtab.nochim)))) #total ASVs
## [1] 641
plot(table(nchar(getSequences(seqtab.nochim)))) #peak at 346bp

Unexpected second peak near 490

Remove ASVs with less than 100 reads total

This threshold has been used before for characterizing pollinator microbiomes (Hammer et al. 2020, 2023). Since my pollens are expected to be a lot more simple than a microbiome, I feel this threshold is quite conservative.

seqtab.nochim<-seqtab.nochim[,!!colSums(seqtab.nochim > 100)]

Citations for this step: Hammer, T. J., J. C. Dickerson, W. O. McMillan, and N. Fierer. 2020. Heliconius Butterflies Host Characteristic and Phylogenetically Structured Adult-Stage Microbiomes. Applied and Environmental Microbiology 86. Hammer, T. J., J. Kueneman, M. Argueta-Guzmán, Q. S. McFrederick, Lady Grant, W. Wcislo, S. Buchmann, and B. N. Danforth. 2023. Bee breweries: The unusually fermentative, lactobacilli-dominated brood cell microbiomes of cellophane bees. Frontiers in Microbiology 14:1–16.

Remove contaminating sequences with decontam

The steps & info below are largely from this tutorial: https://benjjneb.github.io/decontam/vignettes/decontam_intro.html#necessary-ingredients

The investigation of environmental microbial communities and microbiomes has been transformed by the recent widespread adoption of culture-free high-throughput sequencing methods. In amplicon sequencing a particular genetic locus is amplified from DNA extracted from the community of interest, and then sequenced on a next-generation sequencing platform. In shotgun metagenomics, bulk DNA is extracted from the community of interest and sequenced. Both techniques provide cost-effective and culture-free characterizations of microbial communities.

However, the accuracy of these methods is limited in practice by the introduction of contaminating DNA that was not truly present in the sampled community. This contaminating DNA can come from several sources, such as the reagents used in the sequencing reaction, and can critically interfere with downstream analyses, especially in lower biomass environments. The decontam package provides simple statistical methods to identify and visualize contaminating DNA features, allowing them to be removed and a more accurate picture of sampled communities to be constructed from marker-gene and metagenomics data.

###Prep phyloseq objects

##load packages
library(decontam)
library(readxl)
library(tidyverse)
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr     1.1.4     ✔ readr     2.1.5
## ✔ forcats   1.0.0     ✔ stringr   1.5.1
## ✔ lubridate 1.9.3     ✔ tibble    3.2.1
## ✔ purrr     1.0.2     ✔ tidyr     1.3.1
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ lubridate::%within%() masks IRanges::%within%()
## ✖ dplyr::collapse()     masks Biostrings::collapse(), IRanges::collapse()
## ✖ dplyr::combine()      masks Biobase::combine(), BiocGenerics::combine()
## ✖ purrr::compact()      masks XVector::compact()
## ✖ purrr::compose()      masks ShortRead::compose()
## ✖ dplyr::count()        masks matrixStats::count()
## ✖ dplyr::desc()         masks IRanges::desc()
## ✖ tidyr::expand()       masks S4Vectors::expand()
## ✖ dplyr::filter()       masks stats::filter()
## ✖ dplyr::first()        masks GenomicAlignments::first(), S4Vectors::first()
## ✖ dplyr::id()           masks ShortRead::id()
## ✖ dplyr::lag()          masks stats::lag()
## ✖ dplyr::last()         masks GenomicAlignments::last()
## ✖ ggplot2::Position()   masks BiocGenerics::Position(), base::Position()
## ✖ purrr::reduce()       masks GenomicRanges::reduce(), IRanges::reduce()
## ✖ dplyr::rename()       masks S4Vectors::rename()
## ✖ lubridate::second()   masks GenomicAlignments::second(), S4Vectors::second()
## ✖ lubridate::second<-() masks S4Vectors::second<-()
## ✖ dplyr::slice()        masks XVector::slice(), IRanges::slice()
## ✖ tibble::view()        masks ShortRead::view()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
#load sample data
samp.ctrls.conc<-read_excel("/scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/SampleConc.xlsx")
head(samp.ctrls.conc)
## # A tibble: 6 × 5
##   SampleID          SampleID_AllUnderscores Control Conc_ng.uL Note 
##   <chr>             <chr>                   <lgl>        <dbl> <chr>
## 1 ITS2_2020-6-16_H1 ITS2_2020_6_16_H1       FALSE         60.1 <NA> 
## 2 ITS2_2020-6-16_H5 ITS2_2020_6_16_H5       FALSE         53.7 <NA> 
## 3 ITS2_2020-6-16_H6 ITS2_2020_6_16_H6       FALSE         41.8 <NA> 
## 4 ITS2_2020-6-17_H2 ITS2_2020_6_17_H2       FALSE         45.7 <NA> 
## 5 ITS2_2020-6-17_H4 ITS2_2020_6_17_H4       FALSE         75.7 <NA> 
## 6 ITS2_2020-6-17_H8 ITS2_2020_6_17_H8       FALSE         59.6 <NA>
#filter sample data for just ITS2 samples
samp.ctrls.conc <- samp.ctrls.conc %>% filter(str_starts(SampleID,'ITS2'))

detach("package:tidyverse")
#create phyloseq objects with seqtab and sample data (i.e., samp.ctrls.conc)
SAMP <- sample_data(samp.ctrls.conc)
  sample_names(SAMP) <- sample_data(SAMP)$SampleID_AllUnderscores
OTU <- otu_table(seqtab.nochim, taxa_are_rows = F, errorIfNULL=TRUE)
  sample_names(OTU)<-paste0("ITS2_",sample_names(OTU))

#checking if name formats in SAMP and OTU objects match
head(sample_names(SAMP))
## [1] "ITS2_2020_6_16_H1" "ITS2_2020_6_16_H5" "ITS2_2020_6_16_H6"
## [4] "ITS2_2020_6_17_H2" "ITS2_2020_6_17_H4" "ITS2_2020_6_17_H8"
head(sample_names(OTU))
## [1] "ITS2_2020_6_16_H1" "ITS2_2020_6_16_H5" "ITS2_2020_6_16_H6"
## [4] "ITS2_2020_6_17_H2" "ITS2_2020_6_17_H4" "ITS2_2020_6_17_H8"
#checking if number of samples in SAMP and OTU objects match
identical(sample_names(SAMP),sample_names(OTU)) # The safe and reliable way to test two objects for being exactly equal. It returns TRUE in this case, FALSE in every other case.
## [1] FALSE
match(sample_names(SAMP), sample_names(OTU)) # match returns a vector of the positions of (first) matches of its first argument in its second.
##   [1]   1   2   3   4   5   6   7   8   9  10  11  12  13  NA  14  15  16  17
##  [19]  18  19  20  21  22  23  24  25  26  NA  27  28  29  NA  30  31  32  33
##  [37]  34  35  36  37  38  39  40  41  42  43  44  45  46  47  48  49  50  51
##  [55]  52  53  54  55  56  57  58  59  60  61  NA  62  63  64  65  66  67  68
##  [73]  NA  69  70  71  72  73  74  75  76  77  78  79  80  81  82  83  84  85
##  [91]  86  87  88  89  90  91  92  93  94  95  96  97  98  99 100 101 102 103
## [109] 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121
## [127] 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139
## [145] 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157
## [163] 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175
## [181] 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191  NA 192
## [199] 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210
## [217] 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228
## [235] 229 230 231 232 233 234 235 236 237 238 239 240  NA 241 242 243 244 245
## [253]  NA 246 247 248  NA 250 251 252 253 254
sample_names(SAMP) %in% sample_names(OTU) # %in% is a more intuitive interface as a binary operator, which returns a logical vector indicating if there is a match or not for its left operand.
##   [1]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE
##  [13]  TRUE FALSE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE
##  [25]  TRUE  TRUE  TRUE FALSE  TRUE  TRUE  TRUE FALSE  TRUE  TRUE  TRUE  TRUE
##  [37]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE
##  [49]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE
##  [61]  TRUE  TRUE  TRUE  TRUE FALSE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE
##  [73] FALSE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE
##  [85]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE
##  [97]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE
## [109]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE
## [121]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE
## [133]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE
## [145]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE
## [157]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE
## [169]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE
## [181]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE
## [193]  TRUE  TRUE  TRUE  TRUE FALSE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE
## [205]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE
## [217]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE
## [229]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE
## [241]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE FALSE  TRUE  TRUE  TRUE  TRUE  TRUE
## [253] FALSE  TRUE  TRUE  TRUE FALSE  TRUE  TRUE  TRUE  TRUE  TRUE
#subset phyloseq object with sample info to contain only the samples present in the OTU obj
SAMP<-prune_samples(sample_names(SAMP) %in% sample_names(OTU), SAMP) #prune_samples() is a method for pruning/filtering unwanted samples by defining those you want to keep. first argument is a logical vector where the kept samples are TRUE, and length is equal to the number of samples in object x; second argument is the phyloseq object to be pruned (subsetted)

#join phyloseq objects into one
physeq = phyloseq(OTU, SAMP)
physeq
## phyloseq-class experiment-level object
## otu_table()   OTU Table:         [ 345 taxa and 253 samples ]
## sample_data() Sample Data:       [ 253 samples by 5 sample variables ]
slotNames(physeq) #slots for "tax_table", "phy_tree", "refseq" are empty
## [1] "otu_table" "tax_table" "sam_data"  "phy_tree"  "refseq"
#reorder physeq 
physeq.reord <- physeq
otu_table(physeq.reord) <- otu_table(physeq.reord)[order(sample_data(physeq.reord)$Control),] # reorder so the controls appear last

Plots read numbers for control samples and unknown samples

A quick first look at the library sizes (i.e. the number of reads) in each sample, as a function of whether that sample was a true positive sample or a negative control:

#plot read numbers for control vs sample 
df <- as.data.frame(sample_data(physeq)) # Put sample_data into a ggplot-friendly data.frame
df$LibrarySize <- sample_sums(physeq) #sum read numbers
df <- df[order(df$LibrarySize),] #sort by total read numbers
df$Index <- seq(nrow(df)) #create index based on read number sort order
ggplot(data=df, aes(x=Index, y=LibrarySize, color=as.factor(Control))) + geom_point() #plot of read numbers of every library, colored by control vs unk samples

ggplot(data=df, aes(x=Index, y=LibrarySize, color=Conc_ng.uL)) + geom_point() #plot of read numbers of every library, colored by library stock concentration

Identify probable contaminants

The first contaminant identification method we’ll use is the “frequency” method. In this method, the distribution of the frequency of each sequence feature as a function of the input DNA concentration is used to identify contaminants.

The second contaminant identification method is the “prevalence” method. In this method, the prevalence (presence/absence across samples) of each sequence feature in true positive samples is compared to the prevalence in negative controls to identify contaminants.

The final, “combined” method: The frequency and prevalence probabilities are combined with Fisher’s method and used to identify contaminants.

#identify contaminants by frequency & prevalence combined
sample_data(physeq.reord)$is.neg <- sample_data(physeq.reord)$Control == "TRUE"
contamdf.comb <- isContaminant(physeq.reord, method="combined", conc="Conc_ng.uL", neg="is.neg")
## Warning in .is_contaminant(seqtab, conc = conc, neg = neg, method = method, :
## Removed 40 samples with zero total counts (or frequency).
## Warning in .is_contaminant(seqtab, conc = conc, neg = neg, method = method, :
## Removed 40 samples with zero total counts (or frequency).
table(contamdf.comb$contaminant)
## 
## FALSE  TRUE 
##   344     1
which(contamdf.comb$contaminant)
## [1] 131
# Make phyloseq object of presence-absence in negative controls and true samples
ps.pa <- transform_sample_counts(physeq.reord, function(abund) 1*(abund>0))
ps.pa.neg <- prune_samples(sample_data(ps.pa)$Control == "TRUE", ps.pa)
ps.pa.pos <- prune_samples(sample_data(ps.pa)$Control == "FALSE", ps.pa)
# Make data.frame of prevalence in positive and negative samples
df.pa <- data.frame(pa.pos=taxa_sums(ps.pa.pos), pa.neg=taxa_sums(ps.pa.neg),
                      contaminant=contamdf.comb$contaminant)
# Plot the number of times these taxa were observed in negative controls and positive samples
ggplot(data=df.pa, aes(x=pa.neg, y=pa.pos, color=contaminant)) + geom_point() +
  xlab("Prevalence (Negative Controls)") + ylab("Prevalence (True Samples)")

#Samples seem to split pretty cleanly into a branch that shows up mostly in positive samples, and another that shows up mostly in negative controls, and the contaminant assignment (at default probability threshold) has done a good job of identifying those mostly in negative controls.

Remove contaminating sequences

#remove contaminants, create seqtab.nochim.nocontam object
physeq.reord.noncontam <- prune_taxa(!contamdf.comb$contaminant, physeq.reord) #create subsetted phyloseq object with the contaminants removed (pruned)
seqtab.nochim.nocontam <- otu_table(physeq.reord.noncontam) #extract otu table from pruned data
class(seqtab.nochim.nocontam) <- "matrix" #coerce to matrix (so we can manipulate and export more easily)
## Warning in class(seqtab.nochim.nocontam) <- "matrix": Setting class(x) to
## "matrix" sets attribute to NULL; result will no longer be an S4 object
substr(rownames(seqtab.nochim.nocontam), 6, 100) #captures a substring, starting at character 6 (from the left) and continuing up to 100 characters (this will grab sample name without the ITS2 designation)
##   [1] "2020_6_16_H1"                       
##   [2] "2020_6_16_H5"                       
##   [3] "2020_6_16_H6"                       
##   [4] "2020_6_17_H2"                       
##   [5] "2020_6_17_H4"                       
##   [6] "2020_6_17_H8"                       
##   [7] "2020_6_18_H3"                       
##   [8] "2020_6_18_H7"                       
##   [9] "2020_6_18_H9"                       
##  [10] "2020_6_3_H1"                        
##  [11] "2020_6_3_H5"                        
##  [12] "2020_6_3_H6"                        
##  [13] "2020_6_30_H1"                       
##  [14] "2020_6_30_H6"                       
##  [15] "2020_6_4_H2"                        
##  [16] "2020_6_4_H4"                        
##  [17] "2020_6_4_H8"                        
##  [18] "2020_6_5_H3"                        
##  [19] "2020_6_5_H7"                        
##  [20] "2020_6_5_H9"                        
##  [21] "2020_7_1_H2"                        
##  [22] "2020_7_1_H4"                        
##  [23] "2020_7_1_H8"                        
##  [24] "2020_7_14_H1"                       
##  [25] "2020_7_14_H5"                       
##  [26] "2020_7_14_H6"                       
##  [27] "2020_7_15_H4"                       
##  [28] "2020_7_15_H8"                       
##  [29] "2020_7_16_H3"                       
##  [30] "2020_7_16_H9"                       
##  [31] "2020_7_2_H3"                        
##  [32] "2020_7_2_H7"                        
##  [33] "2020_7_2_H9"                        
##  [34] "2021_6_13_H1"                       
##  [35] "2021_6_13_H3"                       
##  [36] "2021_6_14_H11"                      
##  [37] "2021_6_14_H6"                       
##  [38] "2021_6_14_H7"                       
##  [39] "2021_6_15_H8"                       
##  [40] "2021_6_21_H10"                      
##  [41] "2021_6_21_H12"                      
##  [42] "2021_6_21_H9"                       
##  [43] "2021_6_27_H21"                      
##  [44] "2021_6_27_H22"                      
##  [45] "2021_6_27_H27"                      
##  [46] "2021_6_28_H25"                      
##  [47] "2021_6_28_H26"                      
##  [48] "2021_6_28_H28"                      
##  [49] "2021_6_29_H17"                      
##  [50] "2021_6_29_H23"                      
##  [51] "2021_6_29_H24"                      
##  [52] "2021_6_4_H21"                       
##  [53] "2021_6_4_H22"                       
##  [54] "2021_6_4_H27"                       
##  [55] "2021_6_5_H18"                       
##  [56] "2021_6_5_H25"                       
##  [57] "2021_6_5_H26"                       
##  [58] "2021_6_6_H17"                       
##  [59] "2021_6_6_H24"                       
##  [60] "2021_6_7_H23"                       
##  [61] "2021_7_14_H10"                      
##  [62] "2021_7_20_H27"                      
##  [63] "2021_7_21_H25"                      
##  [64] "2021_7_21_H26"                      
##  [65] "2021_7_21_H28"                      
##  [66] "2021_7_6_H11"                       
##  [67] "2021_7_6_H30"                       
##  [68] "2021_7_6_H6"                        
##  [69] "2021_7_7_H8"                        
##  [70] "2021_7_8_H3"                        
##  [71] "2023_6_12_H3"                       
##  [72] "2023_6_12_H5"                       
##  [73] "2023_6_12_H7"                       
##  [74] "2023_6_13_H6"                       
##  [75] "2023_6_13_H8"                       
##  [76] "2023_6_13_H9"                       
##  [77] "2023_6_14_H3"                       
##  [78] "2023_6_14_H7"                       
##  [79] "2023_6_14_H9"                       
##  [80] "2023_6_16_H5"                       
##  [81] "2023_6_24_H6"                       
##  [82] "2023_6_24_H8"                       
##  [83] "2023_6_25_H2"                       
##  [84] "2023_6_25_H4"                       
##  [85] "2023_6_26_H1"                       
##  [86] "2023_6_26_H7"                       
##  [87] "2023_6_27_H3"                       
##  [88] "2023_6_27_H5"                       
##  [89] "2023_6_8_H1"                        
##  [90] "2023_6_8_H2"                        
##  [91] "2023_6_8_H4"                        
##  [92] "2023_6_9_H2"                        
##  [93] "2023_6_9_H4"                        
##  [94] "2023_7_15_H6"                       
##  [95] "2023_7_16_H4"                       
##  [96] "2023_7_17_H1"                       
##  [97] "2023_7_18_H3"                       
##  [98] "2023_7_18_H7"                       
##  [99] "2023_7_29_H5"                       
## [100] "2023_7_29_H7"                       
## [101] "2023_7_30_H8"                       
## [102] "2023_7_30_H9"                       
## [103] "2023_7_5_H1"                        
## [104] "2023_7_5_H2"                        
## [105] "2023_7_5_H4"                        
## [106] "2023_7_6_H6"                        
## [107] "2023_7_6_H8"                        
## [108] "2023_7_6_H9"                        
## [109] "2023_7_8_H3"                        
## [110] "2023_7_8_H5"                        
## [111] "2023_7_8_H7"                        
## [112] "2023_8_4_H2"                        
## [113] "2023_8_4_H5"                        
## [114] "2023_8_4_H6"                        
## [115] "2023_8_4_H7"                        
## [116] "2023_8_4_H8"                        
## [117] "2023_8_4_H9"                        
## [118] "Ba001"                              
## [119] "Ba002"                              
## [120] "Ba003"                              
## [121] "Bb001"                              
## [122] "Bb002"                              
## [123] "Bb003"                              
## [124] "Bb004"                              
## [125] "Bb005"                              
## [126] "Bb007"                              
## [127] "Bb008"                              
## [128] "Bb009"                              
## [129] "Bb010"                              
## [130] "Bb011"                              
## [131] "Bb012"                              
## [132] "Bb013"                              
## [133] "Bb014"                              
## [134] "Bb015"                              
## [135] "Bb016"                              
## [136] "Bb017"                              
## [137] "Bb018"                              
## [138] "Bb019"                              
## [139] "Bb020"                              
## [140] "Bb021"                              
## [141] "Bb022"                              
## [142] "Bb023"                              
## [143] "Bb024"                              
## [144] "Bb025"                              
## [145] "Bf001"                              
## [146] "Bf002"                              
## [147] "Bf003"                              
## [148] "Bf004"                              
## [149] "Bg001"                              
## [150] "Bg002"                              
## [151] "Bg003"                              
## [152] "Bg004"                              
## [153] "Bg005"                              
## [154] "Bg006"                              
## [155] "Bg007"                              
## [156] "Bg008"                              
## [157] "Bg009"                              
## [158] "Bg010"                              
## [159] "Bg011"                              
## [160] "Bg012"                              
## [161] "Bg013"                              
## [162] "Bg014"                              
## [163] "Bg015"                              
## [164] "Bg016"                              
## [165] "Bg017"                              
## [166] "Bg018"                              
## [167] "Bg019"                              
## [168] "Bi001"                              
## [169] "Bi002"                              
## [170] "Bi003"                              
## [171] "Bi004"                              
## [172] "Bi005"                              
## [173] "Bi006"                              
## [174] "Bi007"                              
## [175] "CKC0001"                            
## [176] "ESE0004"                            
## [177] "KLS0007"                            
## [178] "KLS0027"                            
## [179] "KLS0044"                            
## [180] "KLS0045"                            
## [181] "KLS0052"                            
## [182] "KLS0054"                            
## [183] "KLS0055"                            
## [184] "KLS0071"                            
## [185] "KLS0095"                            
## [186] "KLS0096"                            
## [187] "KLS0105"                            
## [188] "KLS0106"                            
## [189] "KLS0119"                            
## [190] "KLS0134"                            
## [191] "KLS0135"                            
## [192] "KLS0136"                            
## [193] "KLS0137"                            
## [194] "KLS0138"                            
## [195] "KLS0139"                            
## [196] "KLS0150"                            
## [197] "KLS0153"                            
## [198] "KLS0155"                            
## [199] "KLS0156"                            
## [200] "KLS0159"                            
## [201] "KLS0163"                            
## [202] "KLS0165"                            
## [203] "KLS0167"                            
## [204] "KLS0168"                            
## [205] "KLS0169"                            
## [206] "KLS0170"                            
## [207] "KLS0200"                            
## [208] "KLS0201"                            
## [209] "KLS0205"                            
## [210] "KLS0209"                            
## [211] "KLS0221"                            
## [212] "KLS0224"                            
## [213] "KLS0225"                            
## [214] "KLS0227"                            
## [215] "KLS0241"                            
## [216] "KLS0244"                            
## [217] "KLS0246"                            
## [218] "KLS0248"                            
## [219] "KLS0253"                            
## [220] "KLS0254"                            
## [221] "KLS0256"                            
## [222] "KLS0259"                            
## [223] "KLS0263"                            
## [224] "KLS0272"                            
## [225] "SCA0009"                            
## [226] "SCA0010"                            
## [227] "SCA0013"                            
## [228] "ext_neg_ctrl_20230909"              
## [229] "ext_neg_ctrl_20230923"              
## [230] "ext_neg_ctrl_20230924"              
## [231] "ext_neg_ctrl_20231007"              
## [232] "ext_neg_ctrl_20231008"              
## [233] "ext_neg_ctrl_20231009"              
## [234] "ext_neg_ctrl_2024220A"              
## [235] "ext_neg_ctrl_2024220B"              
## [236] "ext_neg_ctrl_2024221A"              
## [237] "ext_neg_ctrl_2024221B"              
## [238] "ext_neg_ctrl_2024222A"              
## [239] "ext_neg_ctrl_2024222B"              
## [240] "ext_neg_ctrl_2024312A"              
## [241] "ext_neg_ctrl_2024312B"              
## [242] "ext_neg_ctrl_2024314A"              
## [243] "ext_neg_ctrl_2024319"               
## [244] "ext_neg_ctrl_2024320"               
## [245] "pcr_its2_neg_ctrl_20231021_20231119"
## [246] "pcr_its2_neg_ctrl_20231022_20231120"
## [247] "pcr_its2_neg_ctrl_20231023"         
## [248] "pcr_its2_neg_ctrl_20240411"         
## [249] "pcr_its2_neg_ctrl_20240417"         
## [250] "pcr_its2_neg_ctrl_20240418A"        
## [251] "pcr_its2_neg_ctrl_20240418B"        
## [252] "pcr_its2_neg_ctrl_20240524"         
## [253] "pcr_its2_neg_ctrl_Saskia_20240411"
identical(substr(rownames(seqtab.nochim.nocontam), 6, 100), rownames(seqtab.nochim)) #they are not in the same order, but this is expected because we had previously reordered nocontam according to total reads
## [1] FALSE
match(substr(rownames(seqtab.nochim.nocontam), 6, 100), rownames(seqtab.nochim)) #returns a vector of the positions of (first) matches of its first argument in its second
##   [1]   1   2   3   4   5   6   7   8   9  10  11  12  13  14  15  16  17  18
##  [19]  19  20  21  22  23  24  25  26  27  28  29  30  31  32  33  34  35  36
##  [37]  37  38  39  40  41  42  43  44  45  46  47  48  49  50  51  52  53  54
##  [55]  55  56  57  58  59  60  61  62  63  64  65  66  67  68  69  70  71  72
##  [73]  73  74  75  76  77  78  79  80  81  82  83  84  85  86  87  88  89  90
##  [91]  91  92  93  94  95  96  97  98  99 100 101 102 103 104 105 106 107 108
## [109] 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126
## [127] 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144
## [145] 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162
## [163] 163 164 165 166 167 168 169 170 171 172 173 174 175 176 194 195 196 197
## [181] 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215
## [199] 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233
## [217] 234 235 236 237 238 239 240 241 252 253 254 177 178 179 180 181 182 183
## [235] 184 185 186 187 188 189 190 191 192 193 242 243 244 245 246 247 248 250
## [253] 251
match(rownames(seqtab.nochim),substr(rownames(seqtab.nochim.nocontam), 6, 100)) #returns a vector of the positions of (first) matches of its first argument in its second (switching the order of the arguments reveals that we lost a sample during decontam processing)
##   [1]   1   2   3   4   5   6   7   8   9  10  11  12  13  14  15  16  17  18
##  [19]  19  20  21  22  23  24  25  26  27  28  29  30  31  32  33  34  35  36
##  [37]  37  38  39  40  41  42  43  44  45  46  47  48  49  50  51  52  53  54
##  [55]  55  56  57  58  59  60  61  62  63  64  65  66  67  68  69  70  71  72
##  [73]  73  74  75  76  77  78  79  80  81  82  83  84  85  86  87  88  89  90
##  [91]  91  92  93  94  95  96  97  98  99 100 101 102 103 104 105 106 107 108
## [109] 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126
## [127] 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144
## [145] 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162
## [163] 163 164 165 166 167 168 169 170 171 172 173 174 175 176 228 229 230 231
## [181] 232 233 234 235 236 237 238 239 240 241 242 243 244 177 178 179 180 181
## [199] 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199
## [217] 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217
## [235] 218 219 220 221 222 223 224 245 246 247 248 249 250 251  NA 252 253 225
## [253] 226 227
which(is.na(match(rownames(seqtab.nochim),substr(rownames(seqtab.nochim.nocontam), 6, 100)))) #which nochim sample name is NA (ie not found in the nocontam dataset)
## [1] 249
rownames(seqtab.nochim)[249] #oh yay we lost a negative control!
## [1] "pcr_its2_neg_ctrl_20240517"
index<-paste0("ITS2_",rownames(seqtab.nochim)[-which(is.na(match(rownames(seqtab.nochim),substr(rownames(seqtab.nochim.nocontam), 6, 100))))]) #save the order of sample names in nochim (and paste ITS2_ in front) as an index for reordering nocontam (BUT not including the row with the negative control that got dropped!)

seqtab.nochim.nocontam <- seqtab.nochim.nocontam[index,,drop=FALSE] #reorder nocontam based on order of sample names in nochim

identical(substr(rownames(seqtab.nochim.nocontam), 6, 100),
          rownames(seqtab.nochim)[-which(is.na(match(rownames(seqtab.nochim),
                                                     substr(rownames(seqtab.nochim.nocontam), 6, 100))))]) #true! they match exactly
## [1] TRUE

Track reads through the pipeline

We now inspect the the number of reads that made it through each step in the pipeline to verify everything worked as expected.

# just checking how many samples, reads at various stages
head(out)
##              reads.in reads.out
## 2020_6_16_H1        8         2
## 2020_6_16_H5        5         3
## 2020_6_16_H6        2         1
## 2020_6_17_H2       14         7
## 2020_6_17_H4       21         8
## 2020_6_17_H8        7         5
length(out)/2
## [1] 262
length(dadaFs)
## [1] 254
length(dadaRs)
## [1] 254
length(mergers)
## [1] 254
length(rowSums(seqtab.nochim))
## [1] 254
length(rowSums(seqtab.nochim.nocontam)) #oh.. right we lost a sample at the end
## [1] 253
length(sample.names) 
## [1] 254
#we'll need to add it back so things match up ughhh
       head(rownames(seqtab.nochim.nocontam))
## [1] "ITS2_2020_6_16_H1" "ITS2_2020_6_16_H5" "ITS2_2020_6_16_H6"
## [4] "ITS2_2020_6_17_H2" "ITS2_2020_6_17_H4" "ITS2_2020_6_17_H8"
head(substr(rownames(seqtab.nochim.nocontam), 6, 100))
## [1] "2020_6_16_H1" "2020_6_16_H5" "2020_6_16_H6" "2020_6_17_H2" "2020_6_17_H4"
## [6] "2020_6_17_H8"
which(is.na(match(rownames(seqtab.nochim),substr(rownames(seqtab.nochim.nocontam), 6, 100)))) #which nochim sample name is NA (ie not found in the nocontam dataset)
## [1] 249
rownames(seqtab.nochim)[249]
## [1] "pcr_its2_neg_ctrl_20240517"
seqtab.nochim.nocontam <- rbind(0, seqtab.nochim.nocontam) ## OVERWRITING AN EXISTING OBJECT (do NOT run this multiple times!!)
rownames(seqtab.nochim.nocontam)[rownames(seqtab.nochim.nocontam) == ""] <- "ITS2_pcr_its2_neg_ctrl_20240517"

index<-paste0("ITS2_",rownames(seqtab.nochim)) #save the order of sample names in nochim (and paste ITS2_ in front) as an index for reordering nocontam 

seqtab.nochim.nocontam <- seqtab.nochim.nocontam[index,,drop=FALSE] #reorder nocontam based on order of sample names in nochim

getN <- function(x) sum(getUniques(x))
track <- cbind(out[names(derepFs),], # i only want the samples from "out" which appear in "derepFs" (but in the original tutorial code, you would just call for "out" here)
               sapply(dadaFs, getN), # If processing a single sample, replace with getN(dadaFs)
               sapply(dadaRs, getN),
               sapply(mergers, getN),
               rowSums(seqtab.nochim),
               rowSums(seqtab.nochim.nocontam)
               )

colnames(track) <- c("input", "filtered", "denoisedF", "denoisedR", "merged", "nonchim", "nocontam")
rownames(track) <- sample.names
track
##                                     input filtered denoisedF denoisedR merged
## 2020_6_16_H1                            8        2         1         1      0
## 2020_6_16_H5                            5        3         1         1      0
## 2020_6_16_H6                            2        1         1         1      1
## 2020_6_17_H2                           14        7         1         2      0
## 2020_6_17_H4                           21        8         2         2      0
## 2020_6_17_H8                            7        5         2         1      0
## 2020_6_18_H3                        54831    28544     28396     28339  12098
## 2020_6_18_H7                        22317    14114     14040     13959   6915
## 2020_6_18_H9                        28352     9775      9711      9566   6289
## 2020_6_3_H1                         29280    17562     17415     17348  11248
## 2020_6_3_H5                         33785    17183     16941     16555   5175
## 2020_6_3_H6                         21792     9113      8966      8929   4569
## 2020_6_30_H1                        20012    11400     11254     11212   7602
## 2020_6_30_H6                            3        1         1         1      0
## 2020_6_4_H2                         10665     3807      3677      3100    523
## 2020_6_4_H4                         16915     7207      7097      7057   4726
## 2020_6_4_H8                         38557    20412     20206     19926  11122
## 2020_6_5_H3                         22214    13330     13231     13175   9082
## 2020_6_5_H7                         23419    13763     13686     13546   8180
## 2020_6_5_H9                             6        2         1         1      0
## 2020_7_1_H2                             5        1         1         1      0
## 2020_7_1_H4                             5        3         2         1      0
## 2020_7_1_H8                         95917    59663     59463     59235  43369
## 2020_7_14_H1                          128       54        51        12      0
## 2020_7_14_H5                        60180    25171     25051     24765  14971
## 2020_7_14_H6                        42699    25820     25638     25605   7418
## 2020_7_15_H4                           18        4         1         4      0
## 2020_7_15_H8                           11        3         1         1      0
## 2020_7_16_H3                            7        4         1         2      0
## 2020_7_16_H9                           10        2         1         1      0
## 2020_7_2_H3                         32569    19284     19066     18980   8781
## 2020_7_2_H7                         26559    14455     14327     14295   5466
## 2020_7_2_H9                         13587     7696      7629      7531   4279
## 2021_6_13_H1                        52222    33662     33575     33236  15660
## 2021_6_13_H3                        33682    19584     19421     19277  11578
## 2021_6_14_H11                       42866    30473     30410     30271  16707
## 2021_6_14_H6                        38199    21451     21374     21027  12751
## 2021_6_14_H7                        39022    27667     27597     27472  15278
## 2021_6_15_H8                        45176    29183     29090     28930  12859
## 2021_6_21_H10                       47845    22468     22375     22276  11442
## 2021_6_21_H12                       28369    15386     15032     15104   7963
## 2021_6_21_H9                        50720    22706     22622     22434   9979
## 2021_6_27_H21                       28962    13598     13523     13417   3102
## 2021_6_27_H22                       23010    16586     16506     16061   7729
## 2021_6_27_H27                       19777    11031     10976     10866   4747
## 2021_6_28_H25                       64701    37109     37021     36969  21916
## 2021_6_28_H26                       43084    18011     17891     17837  14493
## 2021_6_28_H28                       46901    24520     24334     24379  15568
## 2021_6_29_H17                       33867    20380     20194     20230  10311
## 2021_6_29_H23                       29020    15119     15055     14912   6896
## 2021_6_29_H24                       41165    23804     23677     23572  12637
## 2021_6_4_H21                        22236     7846      7674      7627   3278
## 2021_6_4_H22                        69217    32343     32201     31571  24879
## 2021_6_4_H27                        12414     4382      4335      4267   2757
## 2021_6_5_H18                        20882     8700      8586      8522   5251
## 2021_6_5_H25                        16223     6167      6082      6027   3509
## 2021_6_5_H26                        53993    30751     30612     30424  21365
## 2021_6_6_H17                        23116     9885      9736      9366   6862
## 2021_6_6_H24                        54777    27479     27276     27229  16440
## 2021_6_7_H23                        30858    10700     10602     10557   5426
## 2021_7_14_H10                       41103    17609     17557     17509  10586
## 2021_7_20_H27                       32048    12038     11956     11900   6471
## 2021_7_21_H25                       22936    16172     16109     16035   7762
## 2021_7_21_H26                          14        6         4         1      0
## 2021_7_21_H28                           4        2         1         1      0
## 2021_7_6_H11                        42801    23260     22998     22830  13299
## 2021_7_6_H30                            2        1         1         1      0
## 2021_7_6_H6                         21771    12438     12280     12261   8306
## 2021_7_7_H8                         32290    23534     23491     23427  11417
## 2021_7_8_H3                         33448    23041     23016     22964  13604
## 2023_6_12_H3                        22492    12263     12057     11929    562
## 2023_6_12_H5                        46692    24829     24669     24679  13128
## 2023_6_12_H7                        16985     6086      6032      5784   1110
## 2023_6_13_H6                        24124    13625     13563     13484   2698
## 2023_6_13_H8                        31042    15490     15367     15408   2908
## 2023_6_13_H9                        29487    19503     19442     19363   2064
## 2023_6_14_H3                        31482    20699     20636     20508   5256
## 2023_6_14_H7                        54210    33188     32955     32946   9490
## 2023_6_14_H9                        57605    37485     37385     37262   7580
## 2023_6_16_H5                        33592    15022     14976     14934   6672
## 2023_6_24_H6                        70528    34675     34422     34361  16009
## 2023_6_24_H8                        33486    17439     17229     17045   4635
## 2023_6_25_H2                        58343    31265     31025     30756   9531
## 2023_6_25_H4                        60706    31537     31350     31364   6982
## 2023_6_26_H1                        15364     8136      8050      7936   1635
## 2023_6_26_H7                        46459    24821     24417     24521   9736
## 2023_6_27_H3                        19522    10606     10515     10494   5163
## 2023_6_27_H5                        31675    16479     16165     16089   7162
## 2023_6_8_H1                         35037    21254     21149     21101   3934
## 2023_6_8_H2                         22807    16527     16484     16344   9485
## 2023_6_8_H4                         62075    38333     38240     38190   2996
## 2023_6_9_H2                         26101    14590     14528     14486   4780
## 2023_6_9_H4                         34416    22545     22358     22339   1051
## 2023_7_15_H6                        53784    23983     23893     23642  17240
## 2023_7_16_H4                        75870    29295     29145     29003  22208
## 2023_7_17_H1                        34448    14894     14699     14670  12309
## 2023_7_18_H3                        38831    21650     21465     21348  14640
## 2023_7_18_H7                        36674    12527     12415     12415  10208
## 2023_7_29_H5                        50259    25406     25314     25279  15083
## 2023_7_29_H7                        60625    40098     39988     39840  30515
## 2023_7_30_H8                        42744    27389     27289     27250  18773
## 2023_7_30_H9                        91667    42773     42490     42577  24512
## 2023_7_5_H1                         28752    18663     18585     18574  13395
## 2023_7_5_H2                         50430    24683     24594     24508  18901
## 2023_7_5_H4                         38538    16886     16793     16724  12854
## 2023_7_6_H6                         51523    23320     23211     23116  18740
## 2023_7_6_H8                         53401    25858     25754     25494  19567
## 2023_7_6_H9                         73700    37973     37821     37646  29072
## 2023_7_8_H3                         29520    14762     14701     14655   8658
## 2023_7_8_H5                         45129    16132     16083     15930   8667
## 2023_7_8_H7                         51405    24378     24153     24042  16093
## 2023_8_4_H2                         37521    23680     23511     23408  14789
## 2023_8_4_H5                         67189    34917     34658     34757  24572
## 2023_8_4_H6                         31419    15791     15595     15424   7729
## 2023_8_4_H7                         41112    19770     19613     19372  12705
## 2023_8_4_H8                         31376    17643     17544     17472  13904
## 2023_8_4_H9                         26434    14039     13929     13653   3926
## Ba001                               20444    10777     10719     10657   2532
## Ba002                               10062     5537      5428      5104    669
## Ba003                               20658     9074      8837      8807   1163
## Bb001                               11483     6275      6162      6154   2744
## Bb002                               13230     7357      7218      7238   3980
## Bb003                               21493    11309     11101     11033   2775
## Bb004                               19719    10220     10097     10000   1821
## Bb005                               10014     5421      5339      5265   2753
## Bb007                                1823     1227      1128      1215    805
## Bb008                                5432     3419      3400      3376   2603
## Bb009                                3344     2193      2149      2159   1600
## Bb010                               20264     8989      8843      8569   3461
## Bb011                                9862     5075      4946      4719   2232
## Bb012                               27072    15928     15826     15646   8121
## Bb013                               14186     6123      5958      5297   2009
## Bb014                                6342     3127      3046      3001   1185
## Bb015                                5798     3045      2944      2884      0
## Bb016                                 570      318       317       301    105
## Bb017                                4100     2279      2226      2189   1291
## Bb018                                9265     5380      5267      5074   1745
## Bb019                               15898     8859      8655      8596   6343
## Bb020                               14554     6218      6130      5936      0
## Bb021                               30914    13981     13748     13348     87
## Bb022                               43003    24593     24464     24138  11416
## Bb023                               50719    24923     24700     24500   7001
## Bb024                               54896    36400     36335     36165   1560
## Bb025                               27360    16550     16341     16420   6032
## Bf001                               50176    22204     22075     21979   5252
## Bf002                               32376    18314     18213     18118    535
## Bf003                               55364    28486     28314     27968    117
## Bf004                               37901    20792     20591     20514    839
## Bg001                               35833    19460     19276     19063   5403
## Bg002                               25237    14410     14203     13954   4965
## Bg003                               53606    31643     31364     30505   5273
## Bg004                               46151    21133     20913     20556   3256
## Bg005                               33617    18459     18343     18194   2314
## Bg006                               67487    30218     30046     29722   9699
## Bg007                               41549    14612     14401     14430   7078
## Bg008                               19916    12218     12138     11972   3054
## Bg009                               38227    21107     21012     20830  10561
## Bg010                               57968    35028     34820     34605   1418
## Bg011                               45087    25569     25343     25049   3272
## Bg012                               53204    32557     32419     32174  11465
## Bg013                               30474    11893     11830     11412    153
## Bg014                               54710    23693     23482     23446   8480
## Bg015                               32118    17641     17481     17363   5360
## Bg016                               27580    15525     15399     15311  11926
## Bg017                               23952    12481     12358     12245   6243
## Bg018                               35296    18766     18585     18070  10936
## Bg019                               33265    16055     15926     15835   7820
## Bi001                               29569    17384     17243     17069   7192
## Bi002                               33740    19912     19718     19661   2960
## Bi003                               24732    12910     12828     12773   4813
## Bi004                               68416    42207     42002     41962   2019
## Bi005                                 159      111       102        96      0
## Bi006                               60367    38312     38052     37963   3284
## Bi007                               48548    30085     29949     29459  18262
## CKC0001                             19033     9923      9900      9791   7687
## ESE0004                             24596    11887     11769     11544   2705
## ext_neg_ctrl_20230909                  45       33        33        20     20
## ext_neg_ctrl_20230923                   2        1         1         1      1
## ext_neg_ctrl_20230924                  10        5         1         4      0
## ext_neg_ctrl_20231007                   6        3         1         1      0
## ext_neg_ctrl_20231008                  83       50        48        48     36
## ext_neg_ctrl_20231009                 586      358       349       338    272
## ext_neg_ctrl_2024220A                 299      131       127        48     44
## ext_neg_ctrl_2024220B                 278      129       120        22      0
## ext_neg_ctrl_2024221A                 325      159       147        44      0
## ext_neg_ctrl_2024221B                 260      130       118        78      9
## ext_neg_ctrl_2024222A                 165       88        69         5      0
## ext_neg_ctrl_2024222B                 121       76        76        54     54
## ext_neg_ctrl_2024312A                 230      104        98        49     49
## ext_neg_ctrl_2024312B                  65       28        27         4      0
## ext_neg_ctrl_2024314A                   2        1         1         1      1
## ext_neg_ctrl_2024319                   37        6         1         2      0
## ext_neg_ctrl_2024320                   28       21        18         2      0
## KLS0007                             10986     4798      4739      4728   2275
## KLS0027                             14230     5767      5734      5649    101
## KLS0044                             18225     8955      8835      8735   1298
## KLS0045                             12411     6222      6142      6134   1656
## KLS0052                             13594     5529      5475      5277   2470
## KLS0054                             30236    16389     16364     16201  12626
## KLS0055                             29020    15797     15781     15613  12197
## KLS0071                             26075    11709     11669     11532   2782
## KLS0095                             19181     8701      8671      8336    316
## KLS0096                             22779    14500     14407     14250   6712
## KLS0105                             31992    19463     19421     19257  15295
## KLS0106                              9438     5682      5640      5471   1776
## KLS0119                             22458    12665     12445     12409   1887
## KLS0134                             23652    11447     11335     11157   3494
## KLS0135                             16804     8081      8020      7795   2260
## KLS0136                              5426     2509      2245      2158      7
## KLS0137                              8678     4076      3967      3811    318
## KLS0138                             15102     6754      6704      6537   1942
## KLS0139                             18858    10020      9900      9815    733
## KLS0150                             28342    18611     18499     18438   3122
## KLS0153                              7713     4536      4447      4405     99
## KLS0155                             36628    17599     17541     17329    126
## KLS0156                             25084    12671     12584     12323   3975
## KLS0159                             16354     9988      9902      9589     56
## KLS0163                             17520     9958      9873      9903   1602
## KLS0165                             19791    12110     12024     11770   1100
## KLS0167                             15401     9019      8777      8860   4210
## KLS0168                             15333     7722      7663      7622   1538
## KLS0169                             16722     8051      7941      7720    340
## KLS0170                             19835     9209      9082      8983    380
## KLS0200                             19713     8381      8275      8203    257
## KLS0201                             48202    26461     26155     26029   8746
## KLS0205                             15124     8493      8341      8356   2235
## KLS0209                             28115    14812     14550     14401   1675
## KLS0221                             33065    20667     20459     20307    814
## KLS0224                             12004     5175      5039      4832    598
## KLS0225                             23561    11502     11320     11219    329
## KLS0227                             26712    11615     11489     11266    495
## KLS0241                             21229    10364     10323     10198    650
## KLS0244                              6280     2924      2852      2791    123
## KLS0246                              9986     4743      4605      4550     58
## KLS0248                             23126     9660      9598      9456   4644
## KLS0253                             13318     6275      6175      6034    771
## KLS0254                             35564    22985     22690     22746   6498
## KLS0256                             13505     7938      7808      7683   3898
## KLS0259                             41395    19483     19302     19159    410
## KLS0263                             23761    11532     11388     11296     91
## KLS0272                             20564    12275     12133     12039    998
## pcr_its2_neg_ctrl_20231021_20231119    17        7         1         2      0
## pcr_its2_neg_ctrl_20231022_20231120     4        1         1         1      0
## pcr_its2_neg_ctrl_20231023             28       12         8         5      0
## pcr_its2_neg_ctrl_20240411             11        5         1         1      0
## pcr_its2_neg_ctrl_20240417            564      260       254        39      0
## pcr_its2_neg_ctrl_20240418A           500      309       304       247    107
## pcr_its2_neg_ctrl_20240418B           129       61        42        28     28
## pcr_its2_neg_ctrl_20240517             73       33        32         1      0
## pcr_its2_neg_ctrl_20240524              7        2         2         2      0
## pcr_its2_neg_ctrl_Saskia_20240411       5        2         2         2      0
## SCA0009                             26242    12498     12290     12206    597
## SCA0010                             30377    13374     13078     12957    617
## SCA0013                             14157     6844      6728      6690    459
##                                     nonchim nocontam
## 2020_6_16_H1                              0        0
## 2020_6_16_H5                              0        0
## 2020_6_16_H6                              0        0
## 2020_6_17_H2                              0        0
## 2020_6_17_H4                              0        0
## 2020_6_17_H8                              0        0
## 2020_6_18_H3                          11038    11038
## 2020_6_18_H7                           6781     6781
## 2020_6_18_H9                           5697     5697
## 2020_6_3_H1                           10917    10917
## 2020_6_3_H5                            4944     4944
## 2020_6_3_H6                            4546     4546
## 2020_6_30_H1                           7225     7225
## 2020_6_30_H6                              0        0
## 2020_6_4_H2                             523      523
## 2020_6_4_H4                            4289     4289
## 2020_6_4_H8                            9863     9863
## 2020_6_5_H3                            8877     8877
## 2020_6_5_H7                            7764     7764
## 2020_6_5_H9                               0        0
## 2020_7_1_H2                               0        0
## 2020_7_1_H4                               0        0
## 2020_7_1_H8                           40336    40336
## 2020_7_14_H1                              0        0
## 2020_7_14_H5                          14708    14708
## 2020_7_14_H6                           6952     6952
## 2020_7_15_H4                              0        0
## 2020_7_15_H8                              0        0
## 2020_7_16_H3                              0        0
## 2020_7_16_H9                              0        0
## 2020_7_2_H3                            8150     8150
## 2020_7_2_H7                            5297     5297
## 2020_7_2_H9                            3893     3893
## 2021_6_13_H1                          15459    15459
## 2021_6_13_H3                          11358    11358
## 2021_6_14_H11                         15735    15735
## 2021_6_14_H6                          12614    12614
## 2021_6_14_H7                          14967    14967
## 2021_6_15_H8                          12735    12735
## 2021_6_21_H10                         10791    10791
## 2021_6_21_H12                          7889     7889
## 2021_6_21_H9                           9258     9258
## 2021_6_27_H21                          2954     2954
## 2021_6_27_H22                          7729     7729
## 2021_6_27_H27                          4634     4634
## 2021_6_28_H25                         20899    20899
## 2021_6_28_H26                         13374    13374
## 2021_6_28_H28                         14508    14508
## 2021_6_29_H17                          9705     9705
## 2021_6_29_H23                          6803     6803
## 2021_6_29_H24                         12487    12487
## 2021_6_4_H21                           2988     2988
## 2021_6_4_H22                          22398    22398
## 2021_6_4_H27                           2515     2515
## 2021_6_5_H18                           4768     4768
## 2021_6_5_H25                           3097     3097
## 2021_6_5_H26                          19676    19676
## 2021_6_6_H17                           6222     6222
## 2021_6_6_H24                          15767    15767
## 2021_6_7_H23                           5313     5313
## 2021_7_14_H10                         10489    10489
## 2021_7_20_H27                          6348     6348
## 2021_7_21_H25                          7317     7317
## 2021_7_21_H26                             0        0
## 2021_7_21_H28                             0        0
## 2021_7_6_H11                          12883    12883
## 2021_7_6_H30                              0        0
## 2021_7_6_H6                            8065     8065
## 2021_7_7_H8                           11328    11328
## 2021_7_8_H3                           13299    13299
## 2023_6_12_H3                            548      548
## 2023_6_12_H5                          12464    12464
## 2023_6_12_H7                            944      944
## 2023_6_13_H6                           2658     2658
## 2023_6_13_H8                           2746     2746
## 2023_6_13_H9                           1927     1927
## 2023_6_14_H3                           5039     5039
## 2023_6_14_H7                           9216     9216
## 2023_6_14_H9                           7030     7030
## 2023_6_16_H5                           6004     6004
## 2023_6_24_H6                          14391    14391
## 2023_6_24_H8                           4052     4052
## 2023_6_25_H2                           8613     8613
## 2023_6_25_H4                           6416     6416
## 2023_6_26_H1                           1548     1548
## 2023_6_26_H7                           9093     9093
## 2023_6_27_H3                           4821     4821
## 2023_6_27_H5                           6635     6635
## 2023_6_8_H1                            3807     3807
## 2023_6_8_H2                            9266     9266
## 2023_6_8_H4                            2834     2834
## 2023_6_9_H2                            4423     4423
## 2023_6_9_H4                             968      968
## 2023_7_15_H6                          16022    16022
## 2023_7_16_H4                          20690    20690
## 2023_7_17_H1                          11213    11213
## 2023_7_18_H3                          12676    12676
## 2023_7_18_H7                           9756     9756
## 2023_7_29_H5                          14614    14614
## 2023_7_29_H7                          29700    29700
## 2023_7_30_H8                          18223    18223
## 2023_7_30_H9                          23429    23429
## 2023_7_5_H1                           12951    12951
## 2023_7_5_H2                           17925    17925
## 2023_7_5_H4                           12203    12203
## 2023_7_6_H6                           17833    17833
## 2023_7_6_H8                           17650    17650
## 2023_7_6_H9                           24678    24678
## 2023_7_8_H3                            8067     8067
## 2023_7_8_H5                            8496     8496
## 2023_7_8_H7                           15459    15459
## 2023_8_4_H2                           14577    14577
## 2023_8_4_H5                           23501    23501
## 2023_8_4_H6                            7460     7460
## 2023_8_4_H7                           11264    11264
## 2023_8_4_H8                           13683    13683
## 2023_8_4_H9                            3455     3455
## Ba001                                  2532     2532
## Ba002                                   620      620
## Ba003                                  1122     1122
## Bb001                                  2592     2592
## Bb002                                  3761     3761
## Bb003                                  2234     2234
## Bb004                                  1395     1395
## Bb005                                  2564     2564
## Bb007                                   765      765
## Bb008                                  1919     1919
## Bb009                                  1401     1401
## Bb010                                  3091     3091
## Bb011                                  2232     2232
## Bb012                                  6951     6951
## Bb013                                  1860     1860
## Bb014                                  1185     1185
## Bb015                                     0        0
## Bb016                                    94       94
## Bb017                                  1291     1291
## Bb018                                  1745     1745
## Bb019                                  5732     5732
## Bb020                                     0        0
## Bb021                                    87       87
## Bb022                                 11255    11255
## Bb023                                  6855     6855
## Bb024                                  1492     1492
## Bb025                                  5579     5579
## Bf001                                  5143     5143
## Bf002                                   506      506
## Bf003                                   101      101
## Bf004                                   738      738
## Bg001                                  5214     5214
## Bg002                                  4531     4531
## Bg003                                  4790     4790
## Bg004                                  2649     2649
## Bg005                                  2244     2244
## Bg006                                  9410     9410
## Bg007                                  7020     7020
## Bg008                                  2712     2712
## Bg009                                 10199    10199
## Bg010                                  1158     1158
## Bg011                                  3096     3096
## Bg012                                 10321    10321
## Bg013                                   153      153
## Bg014                                  8201     8201
## Bg015                                  5135     5135
## Bg016                                 11634    11634
## Bg017                                  5715     5715
## Bg018                                 10706    10706
## Bg019                                  7529     7529
## Bi001                                  6727     6727
## Bi002                                  2773     2773
## Bi003                                  4689     4689
## Bi004                                  1910     1910
## Bi005                                     0        0
## Bi006                                  2804     2804
## Bi007                                 16430    16430
## CKC0001                                7672     7672
## ESE0004                                2446     2446
## ext_neg_ctrl_20230909                     0        0
## ext_neg_ctrl_20230923                     0        0
## ext_neg_ctrl_20230924                     0        0
## ext_neg_ctrl_20231007                     0        0
## ext_neg_ctrl_20231008                     0        0
## ext_neg_ctrl_20231009                   262      262
## ext_neg_ctrl_2024220A                    44       44
## ext_neg_ctrl_2024220B                     0        0
## ext_neg_ctrl_2024221A                     0        0
## ext_neg_ctrl_2024221B                     9        9
## ext_neg_ctrl_2024222A                     0        0
## ext_neg_ctrl_2024222B                    54       54
## ext_neg_ctrl_2024312A                    49       49
## ext_neg_ctrl_2024312B                     0        0
## ext_neg_ctrl_2024314A                     0        0
## ext_neg_ctrl_2024319                      0        0
## ext_neg_ctrl_2024320                      0        0
## KLS0007                                2178     2178
## KLS0027                                 101      101
## KLS0044                                1190     1190
## KLS0045                                1605     1605
## KLS0052                                2470     2470
## KLS0054                               12626    12626
## KLS0055                               12092    12092
## KLS0071                                2782     1676
## KLS0095                                 271      271
## KLS0096                                6645     6645
## KLS0105                               15070    15070
## KLS0106                                1685     1685
## KLS0119                                1729     1578
## KLS0134                                3462     3462
## KLS0135                                2090     2090
## KLS0136                                   7        7
## KLS0137                                 310      310
## KLS0138                                1914     1914
## KLS0139                                 704      704
## KLS0150                                2943     2943
## KLS0153                                  73       73
## KLS0155                                  99       99
## KLS0156                                3836     3836
## KLS0159                                  48       48
## KLS0163                                1602     1602
## KLS0165                                1062     1062
## KLS0167                                4207     4207
## KLS0168                                1345     1345
## KLS0169                                 282      282
## KLS0170                                 380      380
## KLS0200                                 153      153
## KLS0201                                8045     8045
## KLS0205                                2091     2091
## KLS0209                                1396     1396
## KLS0221                                 673      673
## KLS0224                                 577      577
## KLS0225                                  39       39
## KLS0227                                 381      381
## KLS0241                                 608      608
## KLS0244                                 123      123
## KLS0246                                  58       58
## KLS0248                                4368     4368
## KLS0253                                 724      724
## KLS0254                                6176     6176
## KLS0256                                3815     3815
## KLS0259                                 339      339
## KLS0263                                  91       91
## KLS0272                                 917      917
## pcr_its2_neg_ctrl_20231021_20231119       0        0
## pcr_its2_neg_ctrl_20231022_20231120       0        0
## pcr_its2_neg_ctrl_20231023                0        0
## pcr_its2_neg_ctrl_20240411                0        0
## pcr_its2_neg_ctrl_20240417                0        0
## pcr_its2_neg_ctrl_20240418A              69       69
## pcr_its2_neg_ctrl_20240418B              28       28
## pcr_its2_neg_ctrl_20240517                0        0
## pcr_its2_neg_ctrl_20240524                0        0
## pcr_its2_neg_ctrl_Saskia_20240411         0        0
## SCA0009                                 511      511
## SCA0010                                 546      546
## SCA0013                                 405      405
head(track)
##              input filtered denoisedF denoisedR merged nonchim nocontam
## 2020_6_16_H1     8        2         1         1      0       0        0
## 2020_6_16_H5     5        3         1         1      0       0        0
## 2020_6_16_H6     2        1         1         1      1       0        0
## 2020_6_17_H2    14        7         1         2      0       0        0
## 2020_6_17_H4    21        8         2         2      0       0        0
## 2020_6_17_H8     7        5         2         1      0       0        0
track<-as.data.frame(track)

library(tidyverse)
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ lubridate::%within%() masks IRanges::%within%()
## ✖ dplyr::collapse()     masks Biostrings::collapse(), IRanges::collapse()
## ✖ dplyr::combine()      masks Biobase::combine(), BiocGenerics::combine()
## ✖ purrr::compact()      masks XVector::compact()
## ✖ purrr::compose()      masks ShortRead::compose()
## ✖ dplyr::count()        masks matrixStats::count()
## ✖ dplyr::desc()         masks IRanges::desc()
## ✖ tidyr::expand()       masks S4Vectors::expand()
## ✖ dplyr::filter()       masks stats::filter()
## ✖ dplyr::first()        masks GenomicAlignments::first(), S4Vectors::first()
## ✖ dplyr::id()           masks ShortRead::id()
## ✖ dplyr::lag()          masks stats::lag()
## ✖ dplyr::last()         masks GenomicAlignments::last()
## ✖ ggplot2::Position()   masks BiocGenerics::Position(), base::Position()
## ✖ purrr::reduce()       masks GenomicRanges::reduce(), IRanges::reduce()
## ✖ dplyr::rename()       masks S4Vectors::rename()
## ✖ lubridate::second()   masks GenomicAlignments::second(), S4Vectors::second()
## ✖ lubridate::second<-() masks S4Vectors::second<-()
## ✖ dplyr::slice()        masks XVector::slice(), IRanges::slice()
## ✖ tibble::view()        masks ShortRead::view()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
head(track %>% mutate(loss=(input-nocontam)/input)) # calculate % of reads lost from input to final non-chimeric reads
##              input filtered denoisedF denoisedR merged nonchim nocontam loss
## 2020_6_16_H1     8        2         1         1      0       0        0    1
## 2020_6_16_H5     5        3         1         1      0       0        0    1
## 2020_6_16_H6     2        1         1         1      1       0        0    1
## 2020_6_17_H2    14        7         1         2      0       0        0    1
## 2020_6_17_H4    21        8         2         2      0       0        0    1
## 2020_6_17_H8     7        5         2         1      0       0        0    1
head(track %>% filter(str_starts(rownames(.),'ext')|str_starts(rownames(.),'pcr')|str_starts(rownames(.),'rbcL'))) # select just negative control samples
##                       input filtered denoisedF denoisedR merged nonchim
## ext_neg_ctrl_20230909    45       33        33        20     20       0
## ext_neg_ctrl_20230923     2        1         1         1      1       0
## ext_neg_ctrl_20230924    10        5         1         4      0       0
## ext_neg_ctrl_20231007     6        3         1         1      0       0
## ext_neg_ctrl_20231008    83       50        48        48     36       0
## ext_neg_ctrl_20231009   586      358       349       338    272     262
##                       nocontam
## ext_neg_ctrl_20230909        0
## ext_neg_ctrl_20230923        0
## ext_neg_ctrl_20230924        0
## ext_neg_ctrl_20231007        0
## ext_neg_ctrl_20231008        0
## ext_neg_ctrl_20231009      262
# calculate mean and sd for number of reads at each step, separated between negative control and unknown samples
t(track %>% 
    mutate(loss=(input-nocontam)/input) %>% 
    group_by(NegCtrl=str_starts(rownames(.),'ext') | str_starts(rownames(.),'pcr') | str_starts(rownames(.),'rbcL')) %>% 
    summarize(across(input:loss, list(mean=mean, sd=sd), .names="{.col}.{.fn}")) %>% round(.,digits=2)) 
##                    [,1]   [,2]
## NegCtrl            0.00   1.00
## input.mean     29100.57 143.70
## input.sd       18757.64 178.38
## filtered.mean  15447.26  74.63
## filtered.sd    10455.56  98.28
## denoisedF.mean 15326.67  69.70
## denoisedF.sd   10418.87  96.29
## denoisedR.mean 15205.79  38.85
## denoisedR.sd   10391.08  77.39
## merged.mean     6344.93  23.00
## merged.sd       6731.37  55.80
## nonchim.mean    5994.25  19.07
## nonchim.sd      6342.17  52.51
## nocontam.mean   5988.71  19.07
## nocontam.sd     6345.53  52.51
## loss.mean          0.82   0.94
## loss.sd            0.13   0.13
detach("package:tidyverse") #detaching to avoid conflicts... I'll reload it later when I make plots after taxonomic assignment

Assign taxonomy

The DADA2 package provides a native implementation of the naive Bayesian classifier method for taxonomic assignment. The assignTaxonomy function takes as input a set of sequences to ba classified, and a training set of reference sequences with known taxonomy, and outputs taxonomic assignments with at least minBoot bootstrap confidence.

[insert database name & citation]

Load reference databases

# CHANGE ME to location on your machine
PLANiTS.acc   <- "/scratch/kls7sg/Bioinformatics/ReferenceDatabases/ITS-PLANiTS_2020.03.29/ITS2.fasta" # (this database has accession numbers in the header)

# >KU904771.1
# TCAACCCATTGCCCCCTT

PLANiTS.sntx  <- "/scratch/kls7sg/Bioinformatics/ReferenceDatabases/ITS-PLANiTS_2020.03.29/ITS2.SINTAX_format.fas" #this database has headers with the entire taxonomy of the associated sequence, with each taxonomic level is separated by a semicolon

# >KU904771.1;tax=p:Chlorophyta,c:Ulvophyceae,o:Cladophorales,f:Cladophoraceae,g:Basicladia,s:unknown Basicladia ;
# TCAACCCATTGCCCCCTTGC

PLANiTS.sntx.kls <- "/scratch/kls7sg/Bioinformatics/ReferenceDatabases/ITS-PLANiTS_2020.03.29/ITS2.SINTAX_format-kls2.fas" # this database is similar to PLANiTS.sntx but with headers cleaned up to look identical to the format of the rbcL database I used (RBCL Database: Bell, Karen (2021). rbcL July 2021. figshare. Dataset. <https://doi.org/10.6084/m9.figshare.14936007.v1>)

# >k_Viridiplantae;p_Chlorophyta;c_Ulvophyceae;o_Cladophorales;f_Cladophoraceae;g_Basicladia;s_unknown Basicladia 
# TCAACCCATTGCCCCCTTG

UNITE.ref<-"/scratch/kls7sg/Bioinformatics/ReferenceDatabases/ITS-UNITE_2023.07.25/sh_general_release_dynamic_25.07.2023.fasta" #this database
# >Seifertia_sp|KY231246|SH0985654.09FU|reps|k__Fungi;p__Ascomycota;c__Dothideomycetes;o__Pleosporales;f__Melanommataceae;g__Seifertia;s__Seifertia_sp
# CCGTGGGGATTCGTCCCCATTGAGATAGCACCC...

Implement assignTaxonomy function

Sys.time(); t1=Sys.time()
## [1] "2024-11-13 17:04:13 EST"
taxa.its2 <- assignTaxonomy(getSequences(seqtab.nochim.nocontam), PLANiTS.sntx.kls, multithread = TRUE)
Sys.time(); t2=Sys.time()
## [1] "2024-11-13 17:06:38 EST"
#if your reference file is in the incorrect format for assignTaxonomy, check out this webpage: https://benjjneb.github.io/dada2/training.html

t2-t1 
## Time difference of 2.428037 mins
# daaamn, it completed in 1.76 mins (running with 24 cores on Rivanna and multithread=TRUE)

taxa.its2 <- taxa.its2[,-8] #removing an 8th column that only contains NAs (not sure why it got generated...)

##View the taxonomic assignment of all ASV sequences

taxa.its2.print <- taxa.its2; rownames(taxa.its2.print) <- NULL  # Removing sequence rownames for display only
head(taxa.its2.print)
##      Kingdom           Phylum           Class  Order         Family            
## [1,] "k_Viridiplantae" "p_Streptophyta" "c_NA" "o_Lamiales"  "f_Plantaginaceae"
## [2,] "k_Viridiplantae" "p_Streptophyta" "c_NA" "o_Solanales" "f_Solanaceae"    
## [3,] "k_Viridiplantae" "p_Streptophyta" "c_NA" "o_Fabales"   "f_Fabaceae"      
## [4,] "k_Viridiplantae" "p_Streptophyta" "c_NA" "o_Fabales"   "f_Fabaceae"      
## [5,] "k_Viridiplantae" "p_Streptophyta" "c_NA" "o_Fabales"   "f_Fabaceae"      
## [6,] "k_Viridiplantae" "p_Streptophyta" "c_NA" "o_Lamiales"  "f_Plantaginaceae"
##      Genus         Species                
## [1,] "g_Plantago"  NA                     
## [2,] "g_Solanum"   "s_Solanum carolinense"
## [3,] "g_Trifolium" "s_Trifolium repens"   
## [4,] "g_Trifolium" "s_Trifolium repens"   
## [5,] "g_Trifolium" "s_Trifolium repens"   
## [6,] "g_Plantago"  "s_Plantago lanceolata"

Linking taxonomic assignment of ASVs to sample sequence table

its2.seq <- as.data.frame(t(seqtab.nochim.nocontam)) #sample sequence table; transpose columns to rows (so each sequence appears as a row)
its2.taxa <- as.data.frame(taxa.its2) #assigned sequence taxonomy

#do sample sequences appear in the same order as identified sequences?
identical(rownames(its2.seq), rownames(its2.taxa)) # is true, so we proceed
## [1] TRUE
match(rownames(its2.seq),rownames(its2.taxa)) #this function returns the index where the first argument matches the second argument; if the lists are identical, a sequential list of integers up to the total number of records being compared
##   [1]   1   2   3   4   5   6   7   8   9  10  11  12  13  14  15  16  17  18
##  [19]  19  20  21  22  23  24  25  26  27  28  29  30  31  32  33  34  35  36
##  [37]  37  38  39  40  41  42  43  44  45  46  47  48  49  50  51  52  53  54
##  [55]  55  56  57  58  59  60  61  62  63  64  65  66  67  68  69  70  71  72
##  [73]  73  74  75  76  77  78  79  80  81  82  83  84  85  86  87  88  89  90
##  [91]  91  92  93  94  95  96  97  98  99 100 101 102 103 104 105 106 107 108
## [109] 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126
## [127] 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144
## [145] 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162
## [163] 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180
## [181] 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198
## [199] 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216
## [217] 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234
## [235] 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252
## [253] 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270
## [271] 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288
## [289] 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306
## [307] 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324
## [325] 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342
## [343] 343 344
# bind sample sequence table with assigned sequence taxonomy
ITS2.IDs <- cbind(its2.seq,its2.taxa)
# rownames(ITS2.IDs) <- NULL #remove ASV row names (skipping this for now)

#rename samples (remove "ITS2_")
names(ITS2.IDs)
##   [1] "ITS2_2020_6_16_H1"                       
##   [2] "ITS2_2020_6_16_H5"                       
##   [3] "ITS2_2020_6_16_H6"                       
##   [4] "ITS2_2020_6_17_H2"                       
##   [5] "ITS2_2020_6_17_H4"                       
##   [6] "ITS2_2020_6_17_H8"                       
##   [7] "ITS2_2020_6_18_H3"                       
##   [8] "ITS2_2020_6_18_H7"                       
##   [9] "ITS2_2020_6_18_H9"                       
##  [10] "ITS2_2020_6_3_H1"                        
##  [11] "ITS2_2020_6_3_H5"                        
##  [12] "ITS2_2020_6_3_H6"                        
##  [13] "ITS2_2020_6_30_H1"                       
##  [14] "ITS2_2020_6_30_H6"                       
##  [15] "ITS2_2020_6_4_H2"                        
##  [16] "ITS2_2020_6_4_H4"                        
##  [17] "ITS2_2020_6_4_H8"                        
##  [18] "ITS2_2020_6_5_H3"                        
##  [19] "ITS2_2020_6_5_H7"                        
##  [20] "ITS2_2020_6_5_H9"                        
##  [21] "ITS2_2020_7_1_H2"                        
##  [22] "ITS2_2020_7_1_H4"                        
##  [23] "ITS2_2020_7_1_H8"                        
##  [24] "ITS2_2020_7_14_H1"                       
##  [25] "ITS2_2020_7_14_H5"                       
##  [26] "ITS2_2020_7_14_H6"                       
##  [27] "ITS2_2020_7_15_H4"                       
##  [28] "ITS2_2020_7_15_H8"                       
##  [29] "ITS2_2020_7_16_H3"                       
##  [30] "ITS2_2020_7_16_H9"                       
##  [31] "ITS2_2020_7_2_H3"                        
##  [32] "ITS2_2020_7_2_H7"                        
##  [33] "ITS2_2020_7_2_H9"                        
##  [34] "ITS2_2021_6_13_H1"                       
##  [35] "ITS2_2021_6_13_H3"                       
##  [36] "ITS2_2021_6_14_H11"                      
##  [37] "ITS2_2021_6_14_H6"                       
##  [38] "ITS2_2021_6_14_H7"                       
##  [39] "ITS2_2021_6_15_H8"                       
##  [40] "ITS2_2021_6_21_H10"                      
##  [41] "ITS2_2021_6_21_H12"                      
##  [42] "ITS2_2021_6_21_H9"                       
##  [43] "ITS2_2021_6_27_H21"                      
##  [44] "ITS2_2021_6_27_H22"                      
##  [45] "ITS2_2021_6_27_H27"                      
##  [46] "ITS2_2021_6_28_H25"                      
##  [47] "ITS2_2021_6_28_H26"                      
##  [48] "ITS2_2021_6_28_H28"                      
##  [49] "ITS2_2021_6_29_H17"                      
##  [50] "ITS2_2021_6_29_H23"                      
##  [51] "ITS2_2021_6_29_H24"                      
##  [52] "ITS2_2021_6_4_H21"                       
##  [53] "ITS2_2021_6_4_H22"                       
##  [54] "ITS2_2021_6_4_H27"                       
##  [55] "ITS2_2021_6_5_H18"                       
##  [56] "ITS2_2021_6_5_H25"                       
##  [57] "ITS2_2021_6_5_H26"                       
##  [58] "ITS2_2021_6_6_H17"                       
##  [59] "ITS2_2021_6_6_H24"                       
##  [60] "ITS2_2021_6_7_H23"                       
##  [61] "ITS2_2021_7_14_H10"                      
##  [62] "ITS2_2021_7_20_H27"                      
##  [63] "ITS2_2021_7_21_H25"                      
##  [64] "ITS2_2021_7_21_H26"                      
##  [65] "ITS2_2021_7_21_H28"                      
##  [66] "ITS2_2021_7_6_H11"                       
##  [67] "ITS2_2021_7_6_H30"                       
##  [68] "ITS2_2021_7_6_H6"                        
##  [69] "ITS2_2021_7_7_H8"                        
##  [70] "ITS2_2021_7_8_H3"                        
##  [71] "ITS2_2023_6_12_H3"                       
##  [72] "ITS2_2023_6_12_H5"                       
##  [73] "ITS2_2023_6_12_H7"                       
##  [74] "ITS2_2023_6_13_H6"                       
##  [75] "ITS2_2023_6_13_H8"                       
##  [76] "ITS2_2023_6_13_H9"                       
##  [77] "ITS2_2023_6_14_H3"                       
##  [78] "ITS2_2023_6_14_H7"                       
##  [79] "ITS2_2023_6_14_H9"                       
##  [80] "ITS2_2023_6_16_H5"                       
##  [81] "ITS2_2023_6_24_H6"                       
##  [82] "ITS2_2023_6_24_H8"                       
##  [83] "ITS2_2023_6_25_H2"                       
##  [84] "ITS2_2023_6_25_H4"                       
##  [85] "ITS2_2023_6_26_H1"                       
##  [86] "ITS2_2023_6_26_H7"                       
##  [87] "ITS2_2023_6_27_H3"                       
##  [88] "ITS2_2023_6_27_H5"                       
##  [89] "ITS2_2023_6_8_H1"                        
##  [90] "ITS2_2023_6_8_H2"                        
##  [91] "ITS2_2023_6_8_H4"                        
##  [92] "ITS2_2023_6_9_H2"                        
##  [93] "ITS2_2023_6_9_H4"                        
##  [94] "ITS2_2023_7_15_H6"                       
##  [95] "ITS2_2023_7_16_H4"                       
##  [96] "ITS2_2023_7_17_H1"                       
##  [97] "ITS2_2023_7_18_H3"                       
##  [98] "ITS2_2023_7_18_H7"                       
##  [99] "ITS2_2023_7_29_H5"                       
## [100] "ITS2_2023_7_29_H7"                       
## [101] "ITS2_2023_7_30_H8"                       
## [102] "ITS2_2023_7_30_H9"                       
## [103] "ITS2_2023_7_5_H1"                        
## [104] "ITS2_2023_7_5_H2"                        
## [105] "ITS2_2023_7_5_H4"                        
## [106] "ITS2_2023_7_6_H6"                        
## [107] "ITS2_2023_7_6_H8"                        
## [108] "ITS2_2023_7_6_H9"                        
## [109] "ITS2_2023_7_8_H3"                        
## [110] "ITS2_2023_7_8_H5"                        
## [111] "ITS2_2023_7_8_H7"                        
## [112] "ITS2_2023_8_4_H2"                        
## [113] "ITS2_2023_8_4_H5"                        
## [114] "ITS2_2023_8_4_H6"                        
## [115] "ITS2_2023_8_4_H7"                        
## [116] "ITS2_2023_8_4_H8"                        
## [117] "ITS2_2023_8_4_H9"                        
## [118] "ITS2_Ba001"                              
## [119] "ITS2_Ba002"                              
## [120] "ITS2_Ba003"                              
## [121] "ITS2_Bb001"                              
## [122] "ITS2_Bb002"                              
## [123] "ITS2_Bb003"                              
## [124] "ITS2_Bb004"                              
## [125] "ITS2_Bb005"                              
## [126] "ITS2_Bb007"                              
## [127] "ITS2_Bb008"                              
## [128] "ITS2_Bb009"                              
## [129] "ITS2_Bb010"                              
## [130] "ITS2_Bb011"                              
## [131] "ITS2_Bb012"                              
## [132] "ITS2_Bb013"                              
## [133] "ITS2_Bb014"                              
## [134] "ITS2_Bb015"                              
## [135] "ITS2_Bb016"                              
## [136] "ITS2_Bb017"                              
## [137] "ITS2_Bb018"                              
## [138] "ITS2_Bb019"                              
## [139] "ITS2_Bb020"                              
## [140] "ITS2_Bb021"                              
## [141] "ITS2_Bb022"                              
## [142] "ITS2_Bb023"                              
## [143] "ITS2_Bb024"                              
## [144] "ITS2_Bb025"                              
## [145] "ITS2_Bf001"                              
## [146] "ITS2_Bf002"                              
## [147] "ITS2_Bf003"                              
## [148] "ITS2_Bf004"                              
## [149] "ITS2_Bg001"                              
## [150] "ITS2_Bg002"                              
## [151] "ITS2_Bg003"                              
## [152] "ITS2_Bg004"                              
## [153] "ITS2_Bg005"                              
## [154] "ITS2_Bg006"                              
## [155] "ITS2_Bg007"                              
## [156] "ITS2_Bg008"                              
## [157] "ITS2_Bg009"                              
## [158] "ITS2_Bg010"                              
## [159] "ITS2_Bg011"                              
## [160] "ITS2_Bg012"                              
## [161] "ITS2_Bg013"                              
## [162] "ITS2_Bg014"                              
## [163] "ITS2_Bg015"                              
## [164] "ITS2_Bg016"                              
## [165] "ITS2_Bg017"                              
## [166] "ITS2_Bg018"                              
## [167] "ITS2_Bg019"                              
## [168] "ITS2_Bi001"                              
## [169] "ITS2_Bi002"                              
## [170] "ITS2_Bi003"                              
## [171] "ITS2_Bi004"                              
## [172] "ITS2_Bi005"                              
## [173] "ITS2_Bi006"                              
## [174] "ITS2_Bi007"                              
## [175] "ITS2_CKC0001"                            
## [176] "ITS2_ESE0004"                            
## [177] "ITS2_ext_neg_ctrl_20230909"              
## [178] "ITS2_ext_neg_ctrl_20230923"              
## [179] "ITS2_ext_neg_ctrl_20230924"              
## [180] "ITS2_ext_neg_ctrl_20231007"              
## [181] "ITS2_ext_neg_ctrl_20231008"              
## [182] "ITS2_ext_neg_ctrl_20231009"              
## [183] "ITS2_ext_neg_ctrl_2024220A"              
## [184] "ITS2_ext_neg_ctrl_2024220B"              
## [185] "ITS2_ext_neg_ctrl_2024221A"              
## [186] "ITS2_ext_neg_ctrl_2024221B"              
## [187] "ITS2_ext_neg_ctrl_2024222A"              
## [188] "ITS2_ext_neg_ctrl_2024222B"              
## [189] "ITS2_ext_neg_ctrl_2024312A"              
## [190] "ITS2_ext_neg_ctrl_2024312B"              
## [191] "ITS2_ext_neg_ctrl_2024314A"              
## [192] "ITS2_ext_neg_ctrl_2024319"               
## [193] "ITS2_ext_neg_ctrl_2024320"               
## [194] "ITS2_KLS0007"                            
## [195] "ITS2_KLS0027"                            
## [196] "ITS2_KLS0044"                            
## [197] "ITS2_KLS0045"                            
## [198] "ITS2_KLS0052"                            
## [199] "ITS2_KLS0054"                            
## [200] "ITS2_KLS0055"                            
## [201] "ITS2_KLS0071"                            
## [202] "ITS2_KLS0095"                            
## [203] "ITS2_KLS0096"                            
## [204] "ITS2_KLS0105"                            
## [205] "ITS2_KLS0106"                            
## [206] "ITS2_KLS0119"                            
## [207] "ITS2_KLS0134"                            
## [208] "ITS2_KLS0135"                            
## [209] "ITS2_KLS0136"                            
## [210] "ITS2_KLS0137"                            
## [211] "ITS2_KLS0138"                            
## [212] "ITS2_KLS0139"                            
## [213] "ITS2_KLS0150"                            
## [214] "ITS2_KLS0153"                            
## [215] "ITS2_KLS0155"                            
## [216] "ITS2_KLS0156"                            
## [217] "ITS2_KLS0159"                            
## [218] "ITS2_KLS0163"                            
## [219] "ITS2_KLS0165"                            
## [220] "ITS2_KLS0167"                            
## [221] "ITS2_KLS0168"                            
## [222] "ITS2_KLS0169"                            
## [223] "ITS2_KLS0170"                            
## [224] "ITS2_KLS0200"                            
## [225] "ITS2_KLS0201"                            
## [226] "ITS2_KLS0205"                            
## [227] "ITS2_KLS0209"                            
## [228] "ITS2_KLS0221"                            
## [229] "ITS2_KLS0224"                            
## [230] "ITS2_KLS0225"                            
## [231] "ITS2_KLS0227"                            
## [232] "ITS2_KLS0241"                            
## [233] "ITS2_KLS0244"                            
## [234] "ITS2_KLS0246"                            
## [235] "ITS2_KLS0248"                            
## [236] "ITS2_KLS0253"                            
## [237] "ITS2_KLS0254"                            
## [238] "ITS2_KLS0256"                            
## [239] "ITS2_KLS0259"                            
## [240] "ITS2_KLS0263"                            
## [241] "ITS2_KLS0272"                            
## [242] "ITS2_pcr_its2_neg_ctrl_20231021_20231119"
## [243] "ITS2_pcr_its2_neg_ctrl_20231022_20231120"
## [244] "ITS2_pcr_its2_neg_ctrl_20231023"         
## [245] "ITS2_pcr_its2_neg_ctrl_20240411"         
## [246] "ITS2_pcr_its2_neg_ctrl_20240417"         
## [247] "ITS2_pcr_its2_neg_ctrl_20240418A"        
## [248] "ITS2_pcr_its2_neg_ctrl_20240418B"        
## [249] "ITS2_pcr_its2_neg_ctrl_20240517"         
## [250] "ITS2_pcr_its2_neg_ctrl_20240524"         
## [251] "ITS2_pcr_its2_neg_ctrl_Saskia_20240411"  
## [252] "ITS2_SCA0009"                            
## [253] "ITS2_SCA0010"                            
## [254] "ITS2_SCA0013"                            
## [255] "Kingdom"                                 
## [256] "Phylum"                                  
## [257] "Class"                                   
## [258] "Order"                                   
## [259] "Family"                                  
## [260] "Genus"                                   
## [261] "Species"
names(ITS2.IDs) <- sub("^ITS2_", "", names(ITS2.IDs)) #remove the "ITS2_" at beginning of column names
names(ITS2.IDs)
##   [1] "2020_6_16_H1"                       
##   [2] "2020_6_16_H5"                       
##   [3] "2020_6_16_H6"                       
##   [4] "2020_6_17_H2"                       
##   [5] "2020_6_17_H4"                       
##   [6] "2020_6_17_H8"                       
##   [7] "2020_6_18_H3"                       
##   [8] "2020_6_18_H7"                       
##   [9] "2020_6_18_H9"                       
##  [10] "2020_6_3_H1"                        
##  [11] "2020_6_3_H5"                        
##  [12] "2020_6_3_H6"                        
##  [13] "2020_6_30_H1"                       
##  [14] "2020_6_30_H6"                       
##  [15] "2020_6_4_H2"                        
##  [16] "2020_6_4_H4"                        
##  [17] "2020_6_4_H8"                        
##  [18] "2020_6_5_H3"                        
##  [19] "2020_6_5_H7"                        
##  [20] "2020_6_5_H9"                        
##  [21] "2020_7_1_H2"                        
##  [22] "2020_7_1_H4"                        
##  [23] "2020_7_1_H8"                        
##  [24] "2020_7_14_H1"                       
##  [25] "2020_7_14_H5"                       
##  [26] "2020_7_14_H6"                       
##  [27] "2020_7_15_H4"                       
##  [28] "2020_7_15_H8"                       
##  [29] "2020_7_16_H3"                       
##  [30] "2020_7_16_H9"                       
##  [31] "2020_7_2_H3"                        
##  [32] "2020_7_2_H7"                        
##  [33] "2020_7_2_H9"                        
##  [34] "2021_6_13_H1"                       
##  [35] "2021_6_13_H3"                       
##  [36] "2021_6_14_H11"                      
##  [37] "2021_6_14_H6"                       
##  [38] "2021_6_14_H7"                       
##  [39] "2021_6_15_H8"                       
##  [40] "2021_6_21_H10"                      
##  [41] "2021_6_21_H12"                      
##  [42] "2021_6_21_H9"                       
##  [43] "2021_6_27_H21"                      
##  [44] "2021_6_27_H22"                      
##  [45] "2021_6_27_H27"                      
##  [46] "2021_6_28_H25"                      
##  [47] "2021_6_28_H26"                      
##  [48] "2021_6_28_H28"                      
##  [49] "2021_6_29_H17"                      
##  [50] "2021_6_29_H23"                      
##  [51] "2021_6_29_H24"                      
##  [52] "2021_6_4_H21"                       
##  [53] "2021_6_4_H22"                       
##  [54] "2021_6_4_H27"                       
##  [55] "2021_6_5_H18"                       
##  [56] "2021_6_5_H25"                       
##  [57] "2021_6_5_H26"                       
##  [58] "2021_6_6_H17"                       
##  [59] "2021_6_6_H24"                       
##  [60] "2021_6_7_H23"                       
##  [61] "2021_7_14_H10"                      
##  [62] "2021_7_20_H27"                      
##  [63] "2021_7_21_H25"                      
##  [64] "2021_7_21_H26"                      
##  [65] "2021_7_21_H28"                      
##  [66] "2021_7_6_H11"                       
##  [67] "2021_7_6_H30"                       
##  [68] "2021_7_6_H6"                        
##  [69] "2021_7_7_H8"                        
##  [70] "2021_7_8_H3"                        
##  [71] "2023_6_12_H3"                       
##  [72] "2023_6_12_H5"                       
##  [73] "2023_6_12_H7"                       
##  [74] "2023_6_13_H6"                       
##  [75] "2023_6_13_H8"                       
##  [76] "2023_6_13_H9"                       
##  [77] "2023_6_14_H3"                       
##  [78] "2023_6_14_H7"                       
##  [79] "2023_6_14_H9"                       
##  [80] "2023_6_16_H5"                       
##  [81] "2023_6_24_H6"                       
##  [82] "2023_6_24_H8"                       
##  [83] "2023_6_25_H2"                       
##  [84] "2023_6_25_H4"                       
##  [85] "2023_6_26_H1"                       
##  [86] "2023_6_26_H7"                       
##  [87] "2023_6_27_H3"                       
##  [88] "2023_6_27_H5"                       
##  [89] "2023_6_8_H1"                        
##  [90] "2023_6_8_H2"                        
##  [91] "2023_6_8_H4"                        
##  [92] "2023_6_9_H2"                        
##  [93] "2023_6_9_H4"                        
##  [94] "2023_7_15_H6"                       
##  [95] "2023_7_16_H4"                       
##  [96] "2023_7_17_H1"                       
##  [97] "2023_7_18_H3"                       
##  [98] "2023_7_18_H7"                       
##  [99] "2023_7_29_H5"                       
## [100] "2023_7_29_H7"                       
## [101] "2023_7_30_H8"                       
## [102] "2023_7_30_H9"                       
## [103] "2023_7_5_H1"                        
## [104] "2023_7_5_H2"                        
## [105] "2023_7_5_H4"                        
## [106] "2023_7_6_H6"                        
## [107] "2023_7_6_H8"                        
## [108] "2023_7_6_H9"                        
## [109] "2023_7_8_H3"                        
## [110] "2023_7_8_H5"                        
## [111] "2023_7_8_H7"                        
## [112] "2023_8_4_H2"                        
## [113] "2023_8_4_H5"                        
## [114] "2023_8_4_H6"                        
## [115] "2023_8_4_H7"                        
## [116] "2023_8_4_H8"                        
## [117] "2023_8_4_H9"                        
## [118] "Ba001"                              
## [119] "Ba002"                              
## [120] "Ba003"                              
## [121] "Bb001"                              
## [122] "Bb002"                              
## [123] "Bb003"                              
## [124] "Bb004"                              
## [125] "Bb005"                              
## [126] "Bb007"                              
## [127] "Bb008"                              
## [128] "Bb009"                              
## [129] "Bb010"                              
## [130] "Bb011"                              
## [131] "Bb012"                              
## [132] "Bb013"                              
## [133] "Bb014"                              
## [134] "Bb015"                              
## [135] "Bb016"                              
## [136] "Bb017"                              
## [137] "Bb018"                              
## [138] "Bb019"                              
## [139] "Bb020"                              
## [140] "Bb021"                              
## [141] "Bb022"                              
## [142] "Bb023"                              
## [143] "Bb024"                              
## [144] "Bb025"                              
## [145] "Bf001"                              
## [146] "Bf002"                              
## [147] "Bf003"                              
## [148] "Bf004"                              
## [149] "Bg001"                              
## [150] "Bg002"                              
## [151] "Bg003"                              
## [152] "Bg004"                              
## [153] "Bg005"                              
## [154] "Bg006"                              
## [155] "Bg007"                              
## [156] "Bg008"                              
## [157] "Bg009"                              
## [158] "Bg010"                              
## [159] "Bg011"                              
## [160] "Bg012"                              
## [161] "Bg013"                              
## [162] "Bg014"                              
## [163] "Bg015"                              
## [164] "Bg016"                              
## [165] "Bg017"                              
## [166] "Bg018"                              
## [167] "Bg019"                              
## [168] "Bi001"                              
## [169] "Bi002"                              
## [170] "Bi003"                              
## [171] "Bi004"                              
## [172] "Bi005"                              
## [173] "Bi006"                              
## [174] "Bi007"                              
## [175] "CKC0001"                            
## [176] "ESE0004"                            
## [177] "ext_neg_ctrl_20230909"              
## [178] "ext_neg_ctrl_20230923"              
## [179] "ext_neg_ctrl_20230924"              
## [180] "ext_neg_ctrl_20231007"              
## [181] "ext_neg_ctrl_20231008"              
## [182] "ext_neg_ctrl_20231009"              
## [183] "ext_neg_ctrl_2024220A"              
## [184] "ext_neg_ctrl_2024220B"              
## [185] "ext_neg_ctrl_2024221A"              
## [186] "ext_neg_ctrl_2024221B"              
## [187] "ext_neg_ctrl_2024222A"              
## [188] "ext_neg_ctrl_2024222B"              
## [189] "ext_neg_ctrl_2024312A"              
## [190] "ext_neg_ctrl_2024312B"              
## [191] "ext_neg_ctrl_2024314A"              
## [192] "ext_neg_ctrl_2024319"               
## [193] "ext_neg_ctrl_2024320"               
## [194] "KLS0007"                            
## [195] "KLS0027"                            
## [196] "KLS0044"                            
## [197] "KLS0045"                            
## [198] "KLS0052"                            
## [199] "KLS0054"                            
## [200] "KLS0055"                            
## [201] "KLS0071"                            
## [202] "KLS0095"                            
## [203] "KLS0096"                            
## [204] "KLS0105"                            
## [205] "KLS0106"                            
## [206] "KLS0119"                            
## [207] "KLS0134"                            
## [208] "KLS0135"                            
## [209] "KLS0136"                            
## [210] "KLS0137"                            
## [211] "KLS0138"                            
## [212] "KLS0139"                            
## [213] "KLS0150"                            
## [214] "KLS0153"                            
## [215] "KLS0155"                            
## [216] "KLS0156"                            
## [217] "KLS0159"                            
## [218] "KLS0163"                            
## [219] "KLS0165"                            
## [220] "KLS0167"                            
## [221] "KLS0168"                            
## [222] "KLS0169"                            
## [223] "KLS0170"                            
## [224] "KLS0200"                            
## [225] "KLS0201"                            
## [226] "KLS0205"                            
## [227] "KLS0209"                            
## [228] "KLS0221"                            
## [229] "KLS0224"                            
## [230] "KLS0225"                            
## [231] "KLS0227"                            
## [232] "KLS0241"                            
## [233] "KLS0244"                            
## [234] "KLS0246"                            
## [235] "KLS0248"                            
## [236] "KLS0253"                            
## [237] "KLS0254"                            
## [238] "KLS0256"                            
## [239] "KLS0259"                            
## [240] "KLS0263"                            
## [241] "KLS0272"                            
## [242] "pcr_its2_neg_ctrl_20231021_20231119"
## [243] "pcr_its2_neg_ctrl_20231022_20231120"
## [244] "pcr_its2_neg_ctrl_20231023"         
## [245] "pcr_its2_neg_ctrl_20240411"         
## [246] "pcr_its2_neg_ctrl_20240417"         
## [247] "pcr_its2_neg_ctrl_20240418A"        
## [248] "pcr_its2_neg_ctrl_20240418B"        
## [249] "pcr_its2_neg_ctrl_20240517"         
## [250] "pcr_its2_neg_ctrl_20240524"         
## [251] "pcr_its2_neg_ctrl_Saskia_20240411"  
## [252] "SCA0009"                            
## [253] "SCA0010"                            
## [254] "SCA0013"                            
## [255] "Kingdom"                            
## [256] "Phylum"                             
## [257] "Class"                              
## [258] "Order"                              
## [259] "Family"                             
## [260] "Genus"                              
## [261] "Species"

Plots and summaries of taxonomic assignments

library(tidyverse)
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
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## ✖ purrr::compose()      masks ShortRead::compose()
## ✖ dplyr::count()        masks matrixStats::count()
## ✖ dplyr::desc()         masks IRanges::desc()
## ✖ tidyr::expand()       masks S4Vectors::expand()
## ✖ dplyr::filter()       masks stats::filter()
## ✖ dplyr::first()        masks GenomicAlignments::first(), S4Vectors::first()
## ✖ dplyr::id()           masks ShortRead::id()
## ✖ dplyr::lag()          masks stats::lag()
## ✖ dplyr::last()         masks GenomicAlignments::last()
## ✖ ggplot2::Position()   masks BiocGenerics::Position(), base::Position()
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## ✖ lubridate::second<-() masks S4Vectors::second<-()
## ✖ dplyr::slice()        masks XVector::slice(), IRanges::slice()
## ✖ tibble::view()        masks ShortRead::view()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

Create long data from its2.IDs (sample reads by ASV, with taxa assigned)

Transpose its2.IDs (ASV table by sample) into long format after calculating total reads for each ASV (each row in its2.IDs). After transposing, calculate total reads for each Sample

its2.IDs<-ITS2.IDs %>% mutate(ASVTotalReads = select(., '2020_6_16_H1': 'SCA0013') %>% rowSums()) # total ASV reads

its2.IDs.long<-its2.IDs %>% pivot_longer(cols = c(where(is.numeric), -ASVTotalReads), names_to = "Sample", values_to = "Reads") %>% filter(Reads>0) %>% group_by(Sample) %>% mutate(SampleTotalReads=sum(Reads)) # total Sample reads

#its2.IDs<-partial_join(its2.IDs,___sample-info-data___,"Sample", "SampleName") #join sample info if you want/have it

Total reads? Total Samples? Reads per sample?

1,359,952 reads across all samples 213 samples with 1+ reads 7 to 40,336 reads per sample (mean = 6,391)

sum(its2.IDs$ASVTotalReads) #1361209 reads after removing low-abundance ASVs (1,359,952 reads after removing contaminants)
## [1] 1359952
its2.IDs %>% select(where(is.numeric), -ASVTotalReads) %>% colnames(.) %>% n_distinct(.) # 254 samples
## [1] 254
n_distinct(its2.IDs.long$Sample) #213 samples after removing low-abundance ASVs
## [1] 213
temp<-as.data.frame(its2.IDs %>% select(where(is.numeric), -ASVTotalReads) %>% colSums(.)) # sum up all the reads for all samples that appear in the its2.IDs dataset (basically an ASV table by sample with taxonomic ids)
colnames(temp)<-"TotalReads" #rename column
temp %>% filter(TotalReads==0) # filter to view just samples with 0 reads (these samples get dropped from the data when this dataset is transformed long into its2.IDs.long)
##                                     TotalReads
## 2020_6_16_H1                                 0
## 2020_6_16_H5                                 0
## 2020_6_16_H6                                 0
## 2020_6_17_H2                                 0
## 2020_6_17_H4                                 0
## 2020_6_17_H8                                 0
## 2020_6_30_H6                                 0
## 2020_6_5_H9                                  0
## 2020_7_1_H2                                  0
## 2020_7_1_H4                                  0
## 2020_7_14_H1                                 0
## 2020_7_15_H4                                 0
## 2020_7_15_H8                                 0
## 2020_7_16_H3                                 0
## 2020_7_16_H9                                 0
## 2021_7_21_H26                                0
## 2021_7_21_H28                                0
## 2021_7_6_H30                                 0
## Bb015                                        0
## Bb020                                        0
## Bi005                                        0
## ext_neg_ctrl_20230909                        0
## ext_neg_ctrl_20230923                        0
## ext_neg_ctrl_20230924                        0
## ext_neg_ctrl_20231007                        0
## ext_neg_ctrl_20231008                        0
## ext_neg_ctrl_2024220B                        0
## ext_neg_ctrl_2024221A                        0
## ext_neg_ctrl_2024222A                        0
## ext_neg_ctrl_2024312B                        0
## ext_neg_ctrl_2024314A                        0
## ext_neg_ctrl_2024319                         0
## ext_neg_ctrl_2024320                         0
## pcr_its2_neg_ctrl_20231021_20231119          0
## pcr_its2_neg_ctrl_20231022_20231120          0
## pcr_its2_neg_ctrl_20231023                   0
## pcr_its2_neg_ctrl_20240411                   0
## pcr_its2_neg_ctrl_20240417                   0
## pcr_its2_neg_ctrl_20240517                   0
## pcr_its2_neg_ctrl_20240524                   0
## pcr_its2_neg_ctrl_Saskia_20240411            0
rm(temp)

hist(its2.IDs.long %>% group_by(Sample) %>% summarise(SumReads=sum(Reads)) %>% select(-Sample) %>% pull(SumReads), xlab="SampleReads", main=NULL) # 

summary(its2.IDs.long %>% group_by(Sample) %>% summarise(SumReads=sum(Reads)) %>% select(-Sample))
##     SumReads    
##  Min.   :    7  
##  1st Qu.: 1401  
##  Median : 4634  
##  Mean   : 6385  
##  3rd Qu.: 9756  
##  Max.   :40336

Plots: reads per sample and total reads by sample vs control

# plot of reads per sample for __negative control samples__ (color coded by above/below 2K reads)
its2.IDs.long %>% filter(str_starts(Sample,'ext')|str_starts(Sample,'pcr')|str_starts(Sample,'its2')) %>% group_by(Sample) %>% summarise(SumReads=sum(Reads)) %>%
  ggplot(aes(x=Sample,y=SumReads, fill=SumReads<2000))+
  geom_col()+
  theme(axis.text.x = element_text(angle = 90, vjust = 1, hjust=1))

#plot of reads per sample for __unknown samples__ (color coded by below/above 2K reads)
its2.IDs.long %>% filter(!str_starts(Sample,'ext')&!str_starts(Sample,'pcr')&!str_starts(Sample,'its2')) %>% group_by(Sample) %>% summarise(SumReads=sum(Reads)) %>%
  ggplot(aes(x=Sample,y=SumReads, fill=SumReads>2000))+
  geom_col()+
  theme(axis.text.x = element_text(angle = 90, vjust = 1, hjust=1))

#histogram for __unk samples__
its2.IDs.long %>% filter(!str_starts(Sample,'ext')&!str_starts(Sample,'pcr')&!str_starts(Sample,'its2')) %>% group_by(Sample) %>% summarise(SumReads=sum(Reads)) %>%
  ggplot(aes(SumReads))+
  geom_histogram(binwidth = 1000, color="black")

#histogram for __neg ctrls__
its2.IDs.long %>% filter(str_starts(Sample,'ext')|str_starts(Sample,'pcr')|str_starts(Sample,'its2')) %>% group_by(Sample) %>% summarise(SumReads=sum(Reads)) %>%
  ggplot(aes(SumReads))+
  geom_histogram(binwidth = 15, color="black")

How many ASVs total? How many unassigned?

344 total ASVs across all samples 103 of all ASVs were not assigned to species (includes 10 not assigned to genus/family)

length(rownames(its2.IDs)) # 344 total ASVs across all samples
## [1] 344
its2.IDs%>%filter(is.na(Family)) %>% summarize(n=n()) # 4 of all ASVs were not assigned to family
##   n
## 1 4
its2.IDs%>%filter(is.na(Genus)) %>% summarize(n=n()) # 6 of all ASVs were not assigned to genus (includes 4 not assigned to family)
##   n
## 1 6
its2.IDs%>%filter(is.na(Species)) %>% summarize(n=n()) # 103 of all ASVs were not assigned to species (includes 10 not assigned to genus/family)
##     n
## 1 109

How many reads per ASV?

Most ASVs have very few reads.

# most ASVs have very few total reads
ggplot(its2.IDs, aes(x=ASVTotalReads))+
  geom_histogram()
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

(most common genera!) How many reads for each ASV species assignment?

I looked at Genera assignments because so many ASVs were not assigned to species.

ggplot(its2.IDs, aes(x=Genus,y=ASVTotalReads))+
  geom_col()+
  theme(axis.text.x = element_text(angle = 90, vjust = 1, hjust=1))

What percent of reads assigned to spp overall?

Overall, about 80% of reads were assigned to species

its2.IDs %>% filter(is.na(Species)) %>% summarize(sum=sum(ASVTotalReads)) #214,316 reads unassigned to species (out of 1,359,952 reads across all samples total reads)
##      sum
## 1 407522
#after removing low-abund ASVs, there are 285,984 reads unassigned to species (out of 1,898,063 reads total)

(its2.IDs %>% filter(!is.na(Species)) %>% summarize(sum=sum(ASVTotalReads)))/1359952 # ~84% of reads assigned to species; this value may change as the total project reads (denominator) or total assigned reads (numerator) changes with different upstream QC, filtering parameters
##         sum
## 1 0.7003409

What percent of reads assigned to spp for each sample?

some samples with a LOT of unassigned reads how many Unk ASVs per sample

ggplot(its2.IDs.long,aes(x=Sample, y=Reads, fill=!is.na(Species)))+
  geom_col(position = "fill")+
  labs(x="", y="Proportion of Reads")+
  theme(axis.text.x = element_text(angle = 90, vjust = 1, hjust=1))

#some samples with a LOT of unassigned reads

its2.IDs.long %>% filter(is.na(Species)) %>% group_by(Sample) %>% dplyr::summarize(UnkRichness=sum(is.na(Species))) %>%
  ggplot(aes(x=Sample, y=UnkRichness))+
  geom_col()+
  labs(x="",y="Unk ASV Richness")

# how many Unk ASVs per sample

its2.IDs.long %>% group_by(Sample) %>% dplyr::summarize(UnkRichness = sum(is.na(Species)), KnownRichness = sum(!is.na(Species)), UnkProp = UnkRichness/(UnkRichness+KnownRichness))
## # A tibble: 213 × 4
##    Sample       UnkRichness KnownRichness UnkProp
##    <chr>              <int>         <int>   <dbl>
##  1 2020_6_18_H3           4             9   0.308
##  2 2020_6_18_H7           1             7   0.125
##  3 2020_6_18_H9           1             4   0.2  
##  4 2020_6_30_H1           4             8   0.333
##  5 2020_6_3_H1            8             6   0.571
##  6 2020_6_3_H5            2             3   0.4  
##  7 2020_6_3_H6            5             2   0.714
##  8 2020_6_4_H2            0             2   0    
##  9 2020_6_4_H4            3             5   0.375
## 10 2020_6_4_H8            4             7   0.364
## # ℹ 203 more rows
its2.IDs.long %>% group_by(Sample) %>% dplyr::summarize(UnkRichness = sum(is.na(Species)), KnownRichness = sum(!is.na(Species)), UnkProp = UnkRichness/(UnkRichness+KnownRichness)) %>%
  ggplot(aes(x=Sample, y=UnkProp))+
  geom_col()+
  labs(x="",y="Proportion of ASVs Unidentified to Species")

How many unassigned ASVs have more than 1000 reads?

#histogram of ASVs unassigned to species (with more than 1000 reads) 
its2.IDs %>% filter(is.na(Species)&ASVTotalReads>1000) %>% select(ASVTotalReads)%>%
  ggplot(aes(ASVTotalReads))+
  geom_histogram(binwidth = 10000, color="black")

#these 39 ASVs represent ~87% of the Species=NA reads (recall: 214,316 reads unassigned to species)
head(its2.IDs %>% filter(is.na(Species)&ASVTotalReads>1000) %>% select(ASVTotalReads)) # common (>1000 reads) ASVs that were not assigned to species (39 ASVs that comprise a total of 187,416 reads)
##                                                                                                                                                                                                                                                                                                                                                               ASVTotalReads
## TGCAGAATCCCGTGAACCATCGAGTCTTTGAACGCAAGTTGCGCCCGACGCCTTCGGGCTGAGGGCACGCCTGCCTGGGCGTCACGCATCGCGTCGTCCCCTCCCATTCCCTCACGGGTTTGGTTATGGGACGGATAATGGCTTCCCGTTAGCTCGGTTAGCCCAAAAAGGATCCCTCATCGACGGATGTCACAACCAGTGGTGGTTGAAAGATCATTGGTGCTGTTGTGCTTCACCCTGTCGCTTGCTAGGGCATCGTCATAAACTAACGGCGTGTAATGCGCCTTCGACCGCGACCCCAGGTCAGACGGGACTACCCGCTGAGTTTAA                           172989
## TGCAGAATCCCGTGAACCATCGAGTTTTTGAACGCAAGTTGCGCCCGAAGCCATTCGGCCGAGGGCACGTCTGCCTGGGCGTCACGCATCGCGTCGCCCCAGACCACGCCTCCATATGGGGGATGTGTTTGTCTGGGGCGGAGAATGGTCTCCCGTGCCGTTGGCGCGGTTGGCCTAAAAAGGAGTCCCCTTCGACGGACGCACGGCTAGTGGTGGTTGAAAAAGCCTTCGTATCGAGCCGTGTGTCGTTAGCTGCAAGGGAAGCGCTCTCCATAGACCCTAACGTGTCGTCTCGCGACGATGCTTCGACCGCGACCCCAGGTCAGGCGGGACTACCCGCTGAGTTTAA         22666
## TGCAGAATCCCGTGAACCATCGAGTCTTTGAACGCAAGTTGCGCCCGACGCCTTCGGGCTGAGGGCACGCCTGCCTGGGCGTCACGCATCGCGTCGTCCCCTCCCATTCCCTCACGGGTTTGGTTATGGGACGGATAATGGCTTCCCGTTAGCTCGGTTAGCCCAAAAAGGATCCCTCATCGACGGATGTCACAACCAGTGGTGGTTGAAAGATCATTGGTGCTGTTGTGCTTCACCCTGTCGCTTGCTAGGGCATCATCATAAACTAACGGCGTGTAATGCGCCTTCGACCGCGACCCCAGGTCAGACGGGACTACCCGCTGAGTTTAA                            20558
## TGCAGAATCCCGTGAACCATCGAGTCTTTGAACGCAAGTTGCGCCCGAAGCCATTAGGCCGAGGGCACGCCTGCCTGGGCGTCACACGTCGTTGCACCCCCACTACTCCCTCGGGATTGCGGGGTGCGGATGATGGCCTCCCGTACGCTCCGTCGCGCGGTTGGCATAAATACCAAGTCCTCGGCGACGCACGCCACGACAATCGGTGGTTGCGAAACCTCGGTTGCCCGTCGTGTGCGGTCGTCGCGCATCGGGGGCTCGAAAAAATGCTTGGCTCCGGCTTGGCTTTCAACGCGACCCCAGGTCAGGCGGGGTTACCCGCTGAATTTAA                           16425
## TGCAGAATCCCGTGAACCATCGAGTTTTTGAACGCAAGTTGCGCCTGAGACCTTTAGGTTGAGGGCACGTCTGCCTGGGCGTCACACACAGCGTCGCTCCACACCAACCTAGTTGGTAGAGAGCGGATATTGGCCCCCCGAGTCCTTTGGGCACGGTCGGCACAAATATTGGTCCCCGGCAGCGAGTGTCGCGGTCAGCGGTGGTTGTATTTCCTCCAAAGACAAAATGACGCGTTCCTCGTTGCACGTGGATCGAAACGACCCTCGAAAGCCATTTACGGCATTCACCCTGCGACCCCAGGTCAGGCGGGATTACCCGCTGAGTTTAA                             12396
## TGCAGAATCCCGTGAACCATCGAGTCTTTGAACGCAAGTTGCGCCCGAAGCCATTAGGCCGAGGGCACGCCTGCCTGGGCGTCACACGTCGTTGCCCCCCCCAAACCCCTCGGGAGTTGGGCGGGACGGATGATGGCCTCCCGTGTGCTCTGTCATGCGGTTGGCATAAAAACAAGTCCTCGGCGACTAACGCCACGACAATTGGTGGTTGTCAAACCTCTGTTGCCTATCGTGTGCGCGTGTCGAGCGAGGGCTCAACAAACCATGTTGCATCGATTCGTCGATGCTTTCAACGCGACCCCAGGTCAGGCGGGGTTACCCGCTGAATTTAA                          11112
length((its2.IDs %>% filter(is.na(Species)&ASVTotalReads>1000) %>% select(ASVTotalReads))$ASVTotalReads)
## [1] 43
sum(its2.IDs %>% filter(is.na(Species)&ASVTotalReads>1000) %>% select(ASVTotalReads))
## [1] 379882

What percent of ASV richness by sample is left unassigned?

A mean of 30% of ASVs per sample are unassigned to species, but only a mean of 5% of ASVs per sample are unassigned to Family.

# creating a summary table called "ASVs" to count the number of (un)assigned reads and taxonomic richness for each sample
a<-its2.IDs.long %>% group_by(Sample) %>% summarise(SampleTotalReads=sum(Reads))
b<-its2.IDs.long %>% group_by(Sample) %>% summarise(CountASVs=n())
c<-its2.IDs.long %>% group_by(Sample, .drop=FALSE) %>% filter(is.na(Species)) %>% summarise(ASVs_NoSpp=n())
d<-its2.IDs.long %>% group_by(Sample, .drop=FALSE) %>% filter(is.na(Family)) %>% summarise(ASVs_NoFam=n())
e<-its2.IDs.long %>% group_by(Sample, .drop=FALSE) %>% summarise(Families=n_distinct(Family), Genera=n_distinct(Genus))

ASVs <- cbind(a, b[,2],c[,2],d[,2],e[,-1])
ASVs<- ASVs %>% mutate(PercNoSpp = (ASVs_NoSpp/CountASVs)*100, PercNoFam=(ASVs_NoFam/CountASVs)*100) # number and percent of ASVs not assigned to species or family

summary(ASVs)
##     Sample          SampleTotalReads   CountASVs        ASVs_NoSpp   
##  Length:213         Min.   :    7    Min.   : 1.000   Min.   :0.000  
##  Class :character   1st Qu.: 1401    1st Qu.: 4.000   1st Qu.:1.000  
##  Mode  :character   Median : 4634    Median : 7.000   Median :2.000  
##                     Mean   : 6385    Mean   : 7.643   Mean   :2.009  
##                     3rd Qu.: 9756    3rd Qu.:10.000   3rd Qu.:3.000  
##                     Max.   :40336    Max.   :22.000   Max.   :9.000  
##    ASVs_NoFam         Families         Genera         PercNoSpp      
##  Min.   :0.00000   Min.   :1.000   Min.   : 1.000   Min.   :  0.000  
##  1st Qu.:0.00000   1st Qu.:2.000   1st Qu.: 3.000   1st Qu.:  9.091  
##  Median :0.00000   Median :3.000   Median : 4.000   Median : 22.222  
##  Mean   :0.02817   Mean   :3.559   Mean   : 3.892   Mean   : 26.448  
##  3rd Qu.:0.00000   3rd Qu.:5.000   3rd Qu.: 5.000   3rd Qu.: 36.364  
##  Max.   :2.00000   Max.   :9.000   Max.   :10.000   Max.   :100.000  
##    PercNoFam      
##  Min.   : 0.0000  
##  1st Qu.: 0.0000  
##  Median : 0.0000  
##  Mean   : 0.3916  
##  3rd Qu.: 0.0000  
##  Max.   :28.5714
  ggplot(ASVs, aes(x=Sample, y=PercNoSpp))+
  geom_col()

  ggplot(ASVs, aes(x=Sample, y=PercNoFam))+
  geom_col()

How many species per sample?

mean = 3.3 species (range = 1-11 species) per sample

its2.IDs.long %>% filter(!is.na(Species)) %>% group_by(Sample) %>% dplyr::summarize(Richness=n_distinct(Species))
## # A tibble: 203 × 2
##    Sample       Richness
##    <chr>           <int>
##  1 2020_6_18_H3        3
##  2 2020_6_18_H7        2
##  3 2020_6_18_H9        2
##  4 2020_6_30_H1        4
##  5 2020_6_3_H1         2
##  6 2020_6_3_H5         2
##  7 2020_6_3_H6         2
##  8 2020_6_4_H2         2
##  9 2020_6_4_H4         3
## 10 2020_6_4_H8         4
## # ℹ 193 more rows
summary(its2.IDs.long %>% filter(!is.na(Species)) %>% group_by(Sample) %>% dplyr::summarize(Richness=n_distinct(Species)))
##     Sample             Richness     
##  Length:203         Min.   : 1.000  
##  Class :character   1st Qu.: 2.000  
##  Mode  :character   Median : 3.000  
##                     Mean   : 3.217  
##                     3rd Qu.: 4.000  
##                     Max.   :10.000
its2.IDs.long %>% filter(!is.na(Species)) %>% group_by(Sample) %>% dplyr::summarize(Richness=n_distinct(Species)) %>%
  ggplot(aes(x=Sample, y=Richness))+
  geom_col()+
  labs(x="",y="Spp Richness")+
  theme(axis.text.x = element_text(angle = 90, vjust = 1, hjust=1))

How many reads per species per sample? Proportion of reads?

#numbers of reads per species per sample
ggplot(its2.IDs.long,aes(x=Sample, y=Reads, fill=Species))+
  geom_col()+
  labs(x="", y="Num of Reads")+
  theme(axis.text.x = element_text(angle = 90, vjust = 1, hjust=1), legend.position="none")

#the legend for the above plot
grid::grid.newpage()
grid::grid.draw(cowplot::get_legend(ggplot(its2.IDs.long,aes(x=Sample, y=Reads, fill=Species))+geom_col()))
## Warning in get_plot_component(plot, "guide-box"): Multiple components found;
## returning the first one. To return all, use `return_all = TRUE`.

# proportion of reads per species per sample
ggplot(its2.IDs.long,aes(x=Sample, y=Reads, fill=Species))+
  geom_bar(position="fill", stat="identity") +
  labs(x="", y="Prop of Reads")+
  theme(axis.text.x = element_text(angle = 90, vjust = 1, hjust=1), legend.position="none")

Rarefaction with phyloseq

OTU <- otu_table(seqtab.nochim.nocontam, taxa_are_rows = F, errorIfNULL=TRUE)
TAX <- tax_table(taxa.its2)
physeq = phyloseq(OTU, TAX)
physeq
## phyloseq-class experiment-level object
## otu_table()   OTU Table:         [ 344 taxa and 254 samples ]
## tax_table()   Taxonomy Table:    [ 344 taxa by 7 taxonomic ranks ]
slotNames(physeq)
## [1] "otu_table" "tax_table" "sam_data"  "phy_tree"  "refseq"
# example of what you can do with phyloseq object, physeq:
# make plots:
# plot_bar(physeq, fill = "Species") # this is basically the same as the plot under 'how many spp per sample?'


class(OTU) <- "matrix" # as.matrix() will do nothing
## Warning in class(OTU) <- "matrix": Setting class(x) to "matrix" sets attribute
## to NULL; result will no longer be an S4 object
vegan::rarecurve(OTU, step = 50, xlab = "Sample Size", ylab = "Species", label = TRUE, tidy=T) %>%
  ggplot(aes(x=Sample, y=Species, col=Site))+
  geom_line()+
  labs(x="Read Depth", y="ASVs detected", col="")+
  theme(legend.position = "none")+
  lims(x=c(0,25000),y=c(0,25))
## Warning in vegan::rarecurve(OTU, step = 50, xlab = "Sample Size", ylab =
## "Species", : most observed count data have counts 1, but smallest count is 3
## empty rows removed
## Warning: Removed 403 rows containing missing values or values outside the scale range
## (`geom_line()`).

Identify taxa missing from its2 reference database

identify families that are not being identified to species

Histogram of read numbers for each ASV

Using threshold of 1000 reads to designate ‘abundant’ vs ‘non-abundant’ ASVs from “How many unassigned ASVs have more than 1000 reads?” ASVs with this many total reads, but which were unassigned to species should be pulled out for futher investigation

its2.IDs.long %>% ggplot(aes(x=Reads)) + geom_histogram()
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

its2.IDs.long %>% filter(Reads<1000) %>% ggplot(aes(x=Reads)) + geom_histogram()
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

Identify abundant unknown ASVs

Here extract the sequences of abundant (more than 1000 reads) but unidentified (Family or Species is NA) ASVs

its2.IDs.long %>% filter(Reads>1000 & is.na(Species)) %>% ggplot(aes(x=Sample, fill=Family))+geom_bar()

#count sequences of abundant (more than 1000 reads) but unidentified ASVs (Species or Family is NA)
dim(its2.IDs %>% filter(ASVTotalReads>1000 & is.na(Family))) # 0 ASVs
## [1]   0 262
dim(its2.IDs %>% filter(ASVTotalReads>1000 & is.na(Species))) # 39 ASVs
## [1]  43 262
#extract sequences of abundant unidentified ASVs
head(rownames(its2.IDs %>% filter(ASVTotalReads>1000 & is.na(Species))))
## [1] "TGCAGAATCCCGTGAACCATCGAGTCTTTGAACGCAAGTTGCGCCCGACGCCTTCGGGCTGAGGGCACGCCTGCCTGGGCGTCACGCATCGCGTCGTCCCCTCCCATTCCCTCACGGGTTTGGTTATGGGACGGATAATGGCTTCCCGTTAGCTCGGTTAGCCCAAAAAGGATCCCTCATCGACGGATGTCACAACCAGTGGTGGTTGAAAGATCATTGGTGCTGTTGTGCTTCACCCTGTCGCTTGCTAGGGCATCGTCATAAACTAACGGCGTGTAATGCGCCTTCGACCGCGACCCCAGGTCAGACGGGACTACCCGCTGAGTTTAA"                   
## [2] "TGCAGAATCCCGTGAACCATCGAGTTTTTGAACGCAAGTTGCGCCCGAAGCCATTCGGCCGAGGGCACGTCTGCCTGGGCGTCACGCATCGCGTCGCCCCAGACCACGCCTCCATATGGGGGATGTGTTTGTCTGGGGCGGAGAATGGTCTCCCGTGCCGTTGGCGCGGTTGGCCTAAAAAGGAGTCCCCTTCGACGGACGCACGGCTAGTGGTGGTTGAAAAAGCCTTCGTATCGAGCCGTGTGTCGTTAGCTGCAAGGGAAGCGCTCTCCATAGACCCTAACGTGTCGTCTCGCGACGATGCTTCGACCGCGACCCCAGGTCAGGCGGGACTACCCGCTGAGTTTAA"
## [3] "TGCAGAATCCCGTGAACCATCGAGTCTTTGAACGCAAGTTGCGCCCGACGCCTTCGGGCTGAGGGCACGCCTGCCTGGGCGTCACGCATCGCGTCGTCCCCTCCCATTCCCTCACGGGTTTGGTTATGGGACGGATAATGGCTTCCCGTTAGCTCGGTTAGCCCAAAAAGGATCCCTCATCGACGGATGTCACAACCAGTGGTGGTTGAAAGATCATTGGTGCTGTTGTGCTTCACCCTGTCGCTTGCTAGGGCATCATCATAAACTAACGGCGTGTAATGCGCCTTCGACCGCGACCCCAGGTCAGACGGGACTACCCGCTGAGTTTAA"                   
## [4] "TGCAGAATCCCGTGAACCATCGAGTCTTTGAACGCAAGTTGCGCCCGAAGCCATTAGGCCGAGGGCACGCCTGCCTGGGCGTCACACGTCGTTGCACCCCCACTACTCCCTCGGGATTGCGGGGTGCGGATGATGGCCTCCCGTACGCTCCGTCGCGCGGTTGGCATAAATACCAAGTCCTCGGCGACGCACGCCACGACAATCGGTGGTTGCGAAACCTCGGTTGCCCGTCGTGTGCGGTCGTCGCGCATCGGGGGCTCGAAAAAATGCTTGGCTCCGGCTTGGCTTTCAACGCGACCCCAGGTCAGGCGGGGTTACCCGCTGAATTTAA"                  
## [5] "TGCAGAATCCCGTGAACCATCGAGTTTTTGAACGCAAGTTGCGCCTGAGACCTTTAGGTTGAGGGCACGTCTGCCTGGGCGTCACACACAGCGTCGCTCCACACCAACCTAGTTGGTAGAGAGCGGATATTGGCCCCCCGAGTCCTTTGGGCACGGTCGGCACAAATATTGGTCCCCGGCAGCGAGTGTCGCGGTCAGCGGTGGTTGTATTTCCTCCAAAGACAAAATGACGCGTTCCTCGTTGCACGTGGATCGAAACGACCCTCGAAAGCCATTTACGGCATTCACCCTGCGACCCCAGGTCAGGCGGGATTACCCGCTGAGTTTAA"                    
## [6] "TGCAGAATCCCGTGAACCATCGAGTCTTTGAACGCAAGTTGCGCCCGAAGCCATTAGGCCGAGGGCACGCCTGCCTGGGCGTCACACGTCGTTGCCCCCCCCAAACCCCTCGGGAGTTGGGCGGGACGGATGATGGCCTCCCGTGTGCTCTGTCATGCGGTTGGCATAAAAACAAGTCCTCGGCGACTAACGCCACGACAATTGGTGGTTGTCAAACCTCTGTTGCCTATCGTGTGCGCGTGTCGAGCGAGGGCTCAACAAACCATGTTGCATCGATTCGTCGATGCTTTCAACGCGACCCCAGGTCAGGCGGGGTTACCCGCTGAATTTAA"
rownames(its2.IDs %>% filter(ASVTotalReads>1000 & is.na(Species)))[1] #the first ASV
## [1] "TGCAGAATCCCGTGAACCATCGAGTCTTTGAACGCAAGTTGCGCCCGACGCCTTCGGGCTGAGGGCACGCCTGCCTGGGCGTCACGCATCGCGTCGTCCCCTCCCATTCCCTCACGGGTTTGGTTATGGGACGGATAATGGCTTCCCGTTAGCTCGGTTAGCCCAAAAAGGATCCCTCATCGACGGATGTCACAACCAGTGGTGGTTGAAAGATCATTGGTGCTGTTGTGCTTCACCCTGTCGCTTGCTAGGGCATCGTCATAAACTAACGGCGTGTAATGCGCCTTCGACCGCGACCCCAGGTCAGACGGGACTACCCGCTGAGTTTAA"
#" "

BLAST search for the first ASV came back with 100% identity to several Carduus spp (including Carduus acanthoides!!)

View all ASVs with >1000 reads unassigned to species

knitr::kable(its2.IDs %>%
               select(Kingdom:ASVTotalReads) %>%
               filter(ASVTotalReads>1000 & is.na(Species)),
             row.names = FALSE)
Kingdom Phylum Class Order Family Genus Species ASVTotalReads
k_Viridiplantae p_Streptophyta c_NA o_Lamiales f_Plantaginaceae g_Plantago NA 172989
k_Viridiplantae p_Streptophyta c_NA o_Asterales f_Asteraceae g_Carduus NA 22666
k_Viridiplantae p_Streptophyta c_NA o_Lamiales f_Plantaginaceae g_Plantago NA 20558
k_Viridiplantae p_Streptophyta c_NA o_Rosales f_Rosaceae g_Prunus NA 16425
k_Viridiplantae p_Streptophyta c_NA o_Ranunculales f_Ranunculaceae g_Ranunculus NA 12396
k_Viridiplantae p_Streptophyta c_NA o_Rosales f_Rosaceae g_Rubus NA 11112
k_Viridiplantae p_Streptophyta c_NA o_Asterales f_Asteraceae g_Cichorium NA 10335
k_Viridiplantae p_Streptophyta c_NA o_Lamiales f_Oleaceae g_Ligustrum NA 9977
k_Viridiplantae p_Streptophyta c_NA o_Rosales f_Rosaceae g_Prunus NA 6619
k_Viridiplantae p_Streptophyta c_NA o_Rosales f_Rosaceae g_Rubus NA 5945
k_Viridiplantae p_Streptophyta c_NA o_Rosales f_Rosaceae g_Rubus NA 5384
k_Viridiplantae p_Streptophyta c_NA o_Rosales f_Rosaceae g_Prunus NA 5369
k_Viridiplantae p_Streptophyta c_NA o_Asterales f_Asteraceae g_Solidago NA 5003
k_Viridiplantae p_Streptophyta c_NA o_Malpighiales f_Violaceae g_Viola NA 4901
k_Viridiplantae p_Streptophyta c_NA o_Fabales f_Fabaceae g_Trifolium NA 4789
k_Viridiplantae p_Streptophyta c_NA o_Rosales f_Rosaceae g_Rubus NA 4605
k_Viridiplantae p_Streptophyta c_NA o_Rosales f_Rosaceae g_Rubus NA 4439
k_Viridiplantae p_Streptophyta c_NA o_Rosales f_Rosaceae g_Prunus NA 4329
k_Viridiplantae p_Streptophyta c_NA o_Ericales f_Polemoniaceae g_Polemonium NA 3792
k_Viridiplantae p_Streptophyta c_NA o_Asterales f_Asteraceae g_Cichorium NA 3561
k_Viridiplantae p_Streptophyta c_NA o_Rosales f_Rosaceae g_Prunus NA 3375
k_Viridiplantae p_Streptophyta c_NA o_Ericales f_Polemoniaceae g_Polemonium NA 3161
k_Viridiplantae p_Streptophyta c_NA o_Rosales f_Rosaceae g_Photinia NA 2783
k_Viridiplantae p_Streptophyta c_NA o_Malpighiales f_Violaceae g_Viola NA 2719
k_Viridiplantae p_Streptophyta c_NA o_Ranunculales f_Ranunculaceae g_Ranunculus NA 2689
k_Viridiplantae p_Streptophyta c_NA o_Ericales f_Ericaceae g_Vaccinium NA 2663
k_Viridiplantae p_Streptophyta c_NA o_Fagales f_Fagaceae g_Quercus NA 2647
k_Viridiplantae p_Streptophyta c_NA o_Rosales f_Rosaceae g_Prunus NA 2451
k_Viridiplantae p_Streptophyta c_NA o_Lamiales f_Scrophulariaceae g_Verbascum NA 2450
k_Viridiplantae p_Streptophyta c_NA o_Fagales f_Fagaceae g_Quercus NA 2449
k_Viridiplantae p_Streptophyta c_NA o_Rosales f_Rosaceae g_Photinia NA 1857
k_Viridiplantae p_Streptophyta c_NA o_Asterales f_Asteraceae g_Carduus NA 1852
k_Viridiplantae p_Streptophyta c_NA o_Asterales f_Asteraceae g_Solidago NA 1500
k_Viridiplantae p_Streptophyta c_NA o_Rosales f_Rosaceae g_Rosa NA 1424
k_Viridiplantae p_Streptophyta c_NA o_Rosales f_Rosaceae g_Prunus NA 1408
k_Viridiplantae p_Streptophyta c_NA o_Rosales f_Rosaceae g_Photinia NA 1317
k_Viridiplantae p_Streptophyta c_NA o_Ranunculales f_Ranunculaceae g_Ranunculus NA 1306
k_Viridiplantae p_Streptophyta c_NA o_Lamiales f_Oleaceae g_Ligustrum NA 1271
k_Viridiplantae p_Streptophyta c_NA o_Asterales f_Asteraceae g_Centaurea NA 1112
k_Viridiplantae p_Streptophyta c_NA o_Rosales f_Rosaceae g_Photinia NA 1098
k_Viridiplantae p_Streptophyta c_NA o_Fagales f_Fagaceae g_Quercus NA 1074
k_Viridiplantae p_Streptophyta c_NA o_Rosales f_Rosaceae g_Rubus NA 1049
k_Viridiplantae p_Streptophyta c_NA o_Ranunculales f_Ranunculaceae g_Ranunculus NA 1033

Export sequence assignments and accessories for all samples (double check path!)

#writepath:"/scratch/kls7sg/Bioinformatics/RMarkdown/ITS2_bioinformatics_files/"
#altwritepath:"/Users/kelseyschoenemann/Desktop/Bioinformatics/RMarkdown/ITS2_bioinformatics_files"

# save table tracking reads through the pipeline
write.csv(track, file="/scratch/kls7sg/Bioinformatics/RMarkdown/ITS2_bioinformatics_files/track.csv")

# save all ASVs with >1000 reads unassigned to species
save<-as.data.frame(rownames(its2.IDs %>% filter(ASVTotalReads>1000 & is.na(Species))))
write.csv(save, file="/scratch/kls7sg/Bioinformatics/RMarkdown/ITS2_bioinformatics_files/UnkSpp_ITS2_ASVs.csv")

# seqtab.nochim.nocontam for phyloseq obj creation
write.csv(seqtab.nochim.nocontam, file="/scratch/kls7sg/Bioinformatics/RMarkdown/ITS2_bioinformatics_files/seqtab.nochim.nocontam.csv")

# taxa.ITS2 for phyloseq obj creation
write.csv(taxa.its2, file="/scratch/kls7sg/Bioinformatics/RMarkdown/ITS2_bioinformatics_files/taxa.ITS2.csv")

# its2.IDs
write.csv(its2.IDs, file="/scratch/kls7sg/Bioinformatics/RMarkdown/ITS2_bioinformatics_files/its2.IDs.csv")

# its2.IDs.long
write.csv(its2.IDs.long, file="/scratch/kls7sg/Bioinformatics/RMarkdown/ITS2_bioinformatics_files/its2.IDs.long.csv")